50+ Data Science Jobs in India

AI Engineering Lead – Air Cargo Practice

Position Summary

Lead the company's Artificial Intelligence strategy, development, and deployment of AI powered solutions for air cargo revenue management, dynamic pricing, demand forecasting, and optimization. This role combines AI leadership, software engineering, data science, and airline cargo domain expertise to deliver innovative products that improve airline revenue, capacity utilization, and commercial decision-making.

Key Responsibilities -

• Define and execute the AI roadmap aligned with company strategy and product vision.
• Design and deploy AI, Machine Learning, Generative AI, and Agentic AI solutions.
• Build scalable AI platforms, MLOps processes, and governance frameworks.
• Collaborate with product, engineering, commercial, and customer teams.
• Lead and mentor AI engineers and data scientists.
• Support customer engagements, product demonstrations, and thought leadership.

Qualifications -

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Operations Research, Engineering, or related field. -
• 10+ years of experience in AI/ML, software engineering, or advanced analytics.
• 3+ years leading AI, machine learning, or data science teams.
• Expertise in Python, Machine Learning, Deep Learning, Generative and Agentic AI, LLMs, optimization, and cloud platforms
• Experience deploying production-grade AI solutions. - Knowledge of revenue management, pricing, forecasting, or optimization systems.
• Air cargo, airline, logistics, or transportation industry experience preferred. Success Measures
• Deliver AI-powered pricing and revenue optimization capabilities.
• Improve forecast accuracy and pricing effectiveness.
• Launch Agentic AI solutions that automate commercial decision-making.
• Establish scalable AI engineering practices and governance.
• Position the company as an industry leader in AI-driven air cargo revenue management.

Ideal Candidate

A hands-on AI leader who can bridge advanced technology and business value, capable of leading a group of Data Scientists, engaging with airline executives, and delivering innovative AI solutions that drive measurable revenue and profitability improvements.

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.2Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.3Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.4Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.5Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.6Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.7Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.8Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.9Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.10Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered11Mandatory (Age) - Candidate's Age should be below 37 years.

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

Required Qualifications

• 10+ years of experience in data science, marketing analytics, or applied measurement, with 4+ years directly managing and developing data scientists.
• Deep expertise in Marketing Mix Modeling (MMM): methodology, tooling, business integration, and stakeholder communication.
• Strong working knowledge of marketing attribution, incrementality testing, and causal inference methods (geo-testing, diff-in-diff, synthetic controls, uplift modeling).
• Experience with performance forecasting and budget optimization in a marketing context.
• Demonstrated ability to lead a team of data scientists—setting direction, developing careers, and maintaining a high bar for quality and impact.
• Proven ability to manage and influence senior stakeholders across functions and geographies.
• Strong executive communication skills: comfortable presenting complex methodology and business implications to senior marketing and business leaders.
• Deep proficiency in SQL and Python or R; experience operating in production analytics environments.
• Comfort operating in a globally distributed team environment with US-based counterparts.

Nice to Have

• Experience at a high-growth Indian consumer tech company
• Exposure to offline marketing analytics, brand measurement, or upper-funnel attribution.
• Experience scaling and modernizing legacy marketing measurement infrastructure.
• Familiarity with dbt, Databricks, Snowflake, Airflow, or comparable data infrastructure.
• Experience building or managing analytics teams across multiple geographies.

What Sets You Apart

• You build measurement frameworks that marketing leaders actually use to make decisions—not just deliver reports
• You develop high-performing teams, not just high-performing models
• You communicate across the spectrum—from walking an analyst through a causal design to presenting budget implications to a CMO
• You hold a high bar for analytical credibility while being pragmatic about delivery timelines
• You build strong cross-geography partnerships and make distributed teams work effectively
• You stay technically grounded even as your scope grows—you know when to go hands-on and when to step back
• 
  

About the role

You bring experience from organizations where marketing analytics is taken seriously—whether that’s a global technology company, an Indian consumer tech company, a data-driven marketing organization, or a specialist analytics firm. You understand the discipline of marketing science and the craft of building teams that do it well.

Required Qualifications

• 8+ years of hands-on experience in data science, marketing analytics, or applied measurement, Deep expertise in Marketing Mix Modeling (MMM): methodology, tooling, business integration, and stakeholder communication.
• Strong knowledge of marketing attribution, incrementality testing, and causal inference methods (geo-testing, diff-in-diff, synthetic controls, uplift modeling).
• Experience with performance forecasting and budget optimization in a marketing context.
• Proven ability to manage and influence senior stakeholders across functions and geographies.
• Strong executive communication skills: comfortable presenting complex methodology and business implications to senior marketing and business leaders.
• Deep proficiency in SQL and Python or R; experience operating in production analytics environments.
• Comfort operating in a globally distributed team environment with US-based counterparts.

Nice to Have

• Exposure to offline marketing analytics, brand measurement, or upper-funnel attribution.
• Experience scaling and modernizing legacy marketing measurement infrastructure.
• Familiarity with dbt, Databricks, Snowflake, Airflow, or comparable data infrastructure.
• Experience building or managing analytics teams across multiple geographies.
•  

What Sets You Apart

• You build measurement frameworks that marketing leaders actually use to make decisions—not just deliver reports
• You communicate across the spectrum—from walking an analyst through a causal design to presenting budget implications to a CMO
• You hold a high bar for analytical credibility while being pragmatic about delivery timelines
• You build strong cross-geography partnerships 
• You stay technically grounded even as your scope grows—you know when to go hands-on and when to step back

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

12

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

13

Preferred (Experience 1) - Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

14

Preferred (Experience 2) - Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

15

Preferred (Experience 4) - Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

12

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

13

Preferred (Experience 1) - Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

14

Preferred (Experience 2) - Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

15

Preferred (Experience 4) - Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

Are you a Python-savvy developer with experience & portfolio of working on python, AI, ML projects looking to work on innovative projects? Look no further! SJTech Solutions is seeking an ambitious and talented candidate to join our dynamic team. 

Key responsibilities:

1. Develop and implement AI models using Python, Machine Learning, Data Science, and Deep Learning techniques.

2. Working on deep learning and machine learning algorithms

3. Working on automation scripts

4. Working on supervised and unsupervised learning algorithms

5. Stay up-to-date with the latest advancements in AI technology and trends.

If you are passionate about AI and eager to work and grow in a fast-paced environment, we want to hear from you! Apply now!

Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3

Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4

Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5

Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6

Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

7

Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8

Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9

Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10

Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11

Mandatory (Age) - Candidate's Age should be below 37 years.

12

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

13

Preferred (Experience 1) - Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

14

Preferred (Experience 2) - Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

15

Preferred (Experience 4) - Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

About Us :

CLOUDSUFI, a Google Cloud Premier Partner, a Data Science and Product Engineering organization building Products and Solutions for Technology and Enterprise industries. We firmly believe in the power of data to transform businesses and make better decisions. We combine unmatched experience in business processes with cutting edge infrastructure and cloud services. We partner with our customers to monetize their data and make enterprise data dance.

Our Values :

We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.

Equal Opportunity Statement :

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace.

Role : Lead AI/Senior Engineer

Location : Noida, Delhi/NCR

Experience : 3- 9years

Education : BTech / BE / MCA / MSc Computer Science

Job Summary :

We are seeking a highly innovative and skilled AI Engineer to join our AI CoE for the Data Integration Project. The ideal candidate will be responsible for designing, developing, and deploying intelligent assets and AI agents that automate and optimize various stages of the data ingestion and integration pipeline. This role requires expertise in machine learning, natural language processing (NLP), knowledge representation, and cloud platform services, with a strong focus on building scalable and accurate AI solutions.

Key Responsibilities :

- LLM-based Auto-schematization : Develop and refine LLM-based models and techniques for automatically inferring schemas from diverse unstructured and semi-structured public datasets and mapping them to a standardized vocabulary.

- Entity Resolution & ID Generation AI : Design and implement AI models for highly accurate entity resolution, matching new entities with existing IDs and generating unique, standardized IDs for newly identified entities.

- Automated Data Profiling & Schema Detection : Develop AI/ML accelerators for automated data profiling, pattern detection, and schema detection to understand data structure and quality at scale.

- Anomaly Detection & Smart Imputation : Create AI-powered solutions for identifying outliers, inconsistencies, and corrupt records, and for intelligently filling missing values using machine learning algorithms.

- Multilingual Data Integration AI : Develop AI assets for accurately interpreting, translating (leveraging automated tools with human-in-the-loop validation), and semantically mapping data from diverse linguistic sources, preserving meaning and context.

- Validation Automation & Error Pattern Recognition : Build AI agents to run comprehensive data validation tool checks, identify common error types, suggest fixes, and automate common error corrections.

- Knowledge Graph RAG/RIG Integration : Integrate Retrieval Augmented Generation (RAG) and Retrieval Augmented Indexing (RIG) techniques to enhance querying capabilities and facilitate consistency checks within the Knowledge Graph.

- MLOps Implementation : Implement and maintain MLOps practices for the lifecycle management of AI models, including versioning, deployment, monitoring, and retraining on a relevant AI platform.

- Code Generation & Documentation Automation : Develop AI tools for generating reusable scripts, templates, and comprehensive import documentation to streamline development.

- Continuous Improvement Systems : Design and build learning systems, feedback loops, and error analytics mechanisms to continuously improve the accuracy and efficiency of AI-powered automation over time.

Required Skills and Qualifications :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.

- Proven experience (e.g., 3+ years) as an AI/ML Engineer, with a strong portfolio of deployed AI solutions.

- Strong expertise in Natural Language Processing (NLP), including experience with Large Language Models (LLMs) and their applications in data processing.

- Proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).

- Hands-on experience with cloud AI/ML services,

- Understanding of knowledge representation, ontologies (e.g., Schema.org, RDF), and knowledge graphs.

- Experience with data quality, validation, and anomaly detection techniques.

- Familiarity with MLOps principles and practices for model deployment and lifecycle management.

- Strong problem-solving skills and an ability to translate complex data challenges into AI solutions.

- Excellent communication and collaboration skills.

Preferred Qualifications :

- Experience with data integration projects, particularly with large-scale public datasets.

- Familiarity with knowledge graph initiatives.

- Experience with multilingual data processing and AI.

- Contributions to open-source AI/ML projects.

- Experience in an Agile development environment.

Benefits :

- Opportunity to work on a high-impact project at the forefront of AI and data integration.

- Contribute to solidifying a leading data initiative's role as a foundational source for grounding Large Models.

- Access to cutting-edge cloud AI technologies.

- Collaborative, innovative, and fast-paced work environment.

- Significant impact on data quality and operational efficiency.

Senior Gen AI Full Stack Engineer:

• Strong background in AI/ML and Gen AI with a deep understanding of LLMs, NLP pipelines, and AI model lifecycle.

• Experience in designing and building guardrail systems for Gen AI applications – including prompt filtering, semantic validation, toxicity detection, and hallucination mitigation.

• Fast API experience for API development.

• Proficiency in Python with frameworks like LangChain, Transformers, OpenAI, and LLM orchestration tools.

• Strong DevOps skills including CI/CD, Docker, Kubernetes, and Git.

Experience integrating Gen AI models into enterprise platforms securely and ethically.

About the Internship

SkillSecure X is looking for enthusiastic Python Developer Interns who are passionate about software development and programming. This internship provides hands-on experience in Python development through real-world projects, coding assignments, and mentor-guided learning.

Responsibilities

• Develop and maintain Python-based applications.
• Write clean, efficient, and well-documented code.
• Debug, test, and optimize Python programs.
• Work with APIs and databases for application development.
• Collaborate with mentors on project development.
• Complete weekly coding tasks and project assignments.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Object-Oriented Programming (OOP).
• Familiarity with SQL or databases is a plus.
• Basic knowledge of Git is an advantage.
• Strong analytical and problem-solving skills.

Eligibility

• Undergraduate or postgraduate students.
• Recent graduates.
• Students pursuing Computer Science, Information Technology, Software Engineering, Artificial Intelligence, Data Science, or related disciplines.

Benefits

• Hands-on Python development experience.
• Mentor-guided practical training.
• Internship Completion Certificate.
• Letter of Recommendation (based on performance).
• Opportunity to build a strong development portfolio.
• Flexible remote internship.

About SkillSecure X

SkillSecure X is an EdTech and technology company focused on providing industry-oriented training, internships, and real-world project experience in Artificial Intelligence, Data Science, Web Development, Cloud Computing, Cybersecurity, and emerging technologies. Our internship programs are designed to bridge the gap between academic learning and industry requirements through practical assignments, mentor guidance, and project-based learning.

About the Internship

We are looking for motivated and enthusiastic Data Science with AI Interns who are passionate about data analysis, machine learning, and artificial intelligence. This internship provides hands-on exposure to real-world datasets, AI tools, predictive modeling, and data visualization while working on guided industry projects.

This opportunity is ideal for students and recent graduates who want to strengthen their practical skills and build a professional portfolio.

Responsibilities

• Analyze structured and unstructured datasets.
• Clean, preprocess, and transform data for analysis.
• Build basic machine learning models.
• Perform exploratory data analysis (EDA).
• Develop data visualization dashboards and reports.
• Work with Python libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn.
• Learn and apply AI concepts in practical use cases.
• Complete weekly project tasks and assignments.
• Document findings and present project outcomes.
• Collaborate with mentors and fellow interns.

Required Skills

• Basic knowledge of Python programming.
• Understanding of statistics and mathematics fundamentals.
• Familiarity with Data Science concepts.
• Basic understanding of Machine Learning.
• Knowledge of SQL is an added advantage.
• Good analytical and problem-solving skills.
• Strong communication and willingness to learn.

Eligibility

• Undergraduate or postgraduate students.
• Recent graduates.
• Students pursuing Computer Science, Information Technology, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or related disciplines.
• Candidates with a strong interest in AI and Data Science are encouraged to apply.

What You'll Learn

• Python for Data Science
• Data Cleaning & Preprocessing
• Exploratory Data Analysis (EDA)
• Machine Learning Fundamentals
• Artificial Intelligence Concepts
• Data Visualization
• Model Evaluation
• Real-world Project Development
• Professional Documentation
• Industry Best Practices

Internship Benefits

• Hands-on project experience.
• Mentor-guided learning.
• Internship Certificate upon successful completion.
• Letter of Recommendation (based on performance).
• Opportunity to build a professional portfolio.
• Flexible remote working environment.
• Exposure to industry-standard tools and workflows.
• Networking with mentors and peers.

Job Description

Our Media Measurement team uses state-of-the-art technologies and rigorous methods to track who is watching what, where, and how they engage with content. Our clients can evaluate who is consuming which content across different media, platforms and devices, and know what the audience thinks about that content. As people consume media content on more channels, and through more devices, than ever before, we are proud to provide a full view on media consumption.

As Data Scientist you will have following main accountabilities: 

• You own together with your team several of our Data Science solutions throughout the full life cycle (brainstorming, design, implementation, productization and maintenance) 
• You develop solutions based on data science, stats and machine learning models 
• You improve methods and tools. Contribute to our communities of practice in the area of Data Science 
• Communicate with non-data scientists in Tech, Operations, Commercial, Product. Understand the domain and the requirements. Explain Data Science principles, concepts, algorithms, and approaches in simple words to different types of audiences 
• Make data your best friends. Understand their strengths and use them. Be aware of their weaknesses and handle those in your solutions 
• Screen the market for potential new Data Science approaches 
• Foster knowledge exchange within the company. Present GfK's Data Science expertise at conferences and workshops 

Qualifications

Now you know what a Data Scientist does. What skills, qualifications & experience do you need for this job? 

• You typically have a Master's degree or PhD that reflects modeling and statistics skills and 6+ years of experience. 
• You enjoy communicating complex methodology and technology to tech and non tech audiences 
• You have expert statistical / machine learning modeling skills (e.g. statistical tests, classification, predictive modelling, handling of missing data, sampling, weighting) 
• You have experience with an analytical programming language (Python) and the respective ecosystem 

Besides the things we really expect you to have, there are some things which would be amazing if you have experience with them: 

• Knowledge of cloud computing environments and tooling (especially AWS) 
• Advanced software development skills (unit testing, CI/CD, Git) 
• Basic skills regarding database handling as SQL 
• Basic knowledge of the always evolving Data Science ecosystem and its frameworks 

Additional Information

• Enjoy a flexible and rewarding work environment with peer-to-peer recognition platforms. 
• Recharge and revitalize with help of wellness plans made for you and your family. 
• Plan your future with financial wellness tools. 
• Stay relevant and upskill yourself with career development opportunities. 

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

Junior Data Scientist (2–3 Years Experience)

• Strong understanding of Probability & Statistics
• Strong educational background in Statistics or Mathematics (degree/course specialization). 
• Knowledge of core Machine Learning algorithms
• Proficiency in Python
• Experience with Natural Language Processing (NLP)
• Understanding of Transformer-based models
• 2–3 years of hands-on Data Science experience
• Good analytical and problem-solving skills

Senior Data Scientist (ML) – 5+ Years

Required Skills:

• 5+ years of experience in Data Science/ML
• Strong knowledge of Probability & Statistics
• Strong educational background in Statistics or Mathematics (degree/course specialization). 
• Good understanding of core Machine Learning algorithms
• Proficiency in Python, PySpark, and SQL
• Experience with Databricks, Azure ML, SageMaker, or Vertex AI
• Hands-on experience in Natural Language Processing (NLP)
• Understanding of Transformer-based models and architectures
• Ability to build, deploy, and optimize ML solutions at scale

Experience: 6+ years building and operating production ML systems that drive commercial decisions at scale. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pag05ROZwgz5AaLDG/form 

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Terrabase builds decisioning infrastructure for enterprise customers: ranked recommendations, scoring pipelines, and policy-governed outputs that drive real commercial action. Our ML systems do not live in notebooks. They run multi-stage evaluation harnesses, apply structured governance rules, backtest against historical outcomes, and ship ranked outputs that customers act on daily.

This role owns the decisioning system end to end. That means the models, the eval harness, the policy layer, the production services, and the technical roadmap for where all of it goes next.

What You Will Do

Own the decisioning and ranking pipeline. Design, extend, and operate the end-to-end system: candidate generation in DuckDB, multi-stage scoring with LightGBM and AutoGluon, post-score policy application, and final ranked output delivery. You understand each layer well enough to debug latency, correctness, and coverage problems quickly, and to design the next version.

Lead the evaluation harness. Our eval pipeline runs multiple gates before any output ships: data health checks, specification validation, business rules enforcement, resolution checks, LLM-as-judge scoring, backtest against historical outcomes, and final output validation. You will own this harness, extend it as the system grows, and ensure every model or pipeline change is measurable and reproducible before it reaches a customer.

Apply policy logic with rigor. Our ML systems operate under structured governance rules that determine which offers apply to which customer segments, under what conditions. You will implement, test, and audit these rules in code, not configure them in a spreadsheet. Every exclusion must be traceable and explainable.

Engineer features that move metrics. Identify and build the behavioral signals, engagement indicators, contract features, and value-band attributes that improve model performance. Close the loop from feature hypothesis through offline evaluation to production monitoring. Own the data contracts between upstream sources and the scoring pipeline.

Build and maintain the production pipeline and service layer. The decisioning system is not a batch notebook. You will write and operate the Python pipeline and service layer that wraps model inference, handles edge cases, versions model artifacts, and connects to downstream consumers. You own CI, test coverage, reproducible training runs, monitoring, and production incidents.

Drive technical direction. Write design documents, lead code review, and set the engineering standard for the decisioning system. Help define the roadmap: what gets built, in what order, and why. Mentor contributors who work alongside you on this system.

Work forward-deployed. You will engage directly with customer stakeholders to understand business context, interpret model outputs, and translate commercial requirements into system constraints. You are accountable for customer delivery, not just model accuracy.

What We Are Looking For

• 6+ years building and operating production ML systems, not prototypes or research work
• Strong Python skills across the full ML lifecycle: data pipelines, feature engineering, model training, inference services, and monitoring
• Production experience with gradient boosting models (LightGBM, XGBoost)
• Hands-on with DuckDB or similar in-process analytical engines for large-scale data processing
• Evaluation discipline: held-out metrics, backtesting against historical data, multi-gate eval pipelines, LLM-as-judge patterns
• Experience applying business rules, policy overrides, or constraint layers on top of model outputs
• Engineering fundamentals: CI pipelines, data contracts, versioned artifacts, test coverage, incident response
• Technical leadership: design docs, code review, roadmap input, mentoring
• Comfort with forward-deployed work: you can run a meeting with a non-technical stakeholder and turn the output into a system requirement
• Comfort inheriting an existing production codebase, improving its structure, and raising reliability without rewriting everything from scratch

Bonus Points

• Experience with next-best-offer engines, customer-level targeting, or recommendation systems at scale
• Experience with AutoML frameworks (AutoGluon or similar) in a production scoring pipeline
• Thompson sampling, multi-armed bandits, or portfolio-level optimization experience
• Exposure to structured data from telecoms, financial services, or retail sectors
• Prior work owning a decisioning or ranking system as the technical lead

Life at Terrabase

We are a sharp, focused, fully remote team that ships to real enterprise customers weekly. You will own a system that drives measurable commercial outcomes, with high autonomy, generous cloud budgets, and a culture that prizes rigor over hype.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

Website and Company profile:

www.wissen.com

LinkedIn Page:

https://www.linkedin.com/company/wissen-technology/

Company Name – Wissen Technology

Group of companies in India – Wissen Technology & Wissen Infotech

Work Location – Whitefield, Bangalore

While you may already know about Wissen and the company history, here is a quick rundown for you.

About Wissen Technology

• The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.
• Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.
• Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.
• Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.
• Globally present with offices US, India, UK, Australia, Mexico, and Canada.
• We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.
• Wissen Technology has been certified as a Great Place to Work®.
• Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.
• Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.
• We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.

JOB DESCRIPTION

Job Title:

Data Scientist – Graph & Analytics

Location:

Pune, Maharashtra

Work Mode:

Work from Office – 5 Days a Week

Experience:

3–5 Years

Employment Type:

Full-Time

Education:

B.E. / B.Tech in Computer Science, IT, Statistics, or related field

About the Role

We are looking for an analytical and detail-oriented Data Scientist with deep expertise in graph analytics, network analysis, and scalable data engineering. This is not a conventional machine learning role — the focus is on understanding complex relationships, structures, and patterns within large-scale datasets using graph-based methods and statistical modeling. You will work in a collaborative, fast-paced environment and be expected to contribute across the full data lifecycle — from raw data exploration through to production-grade analytical systems.

This is a full-time, in-office role based out of our Pune office (5 days a week).

Key Responsibilities

Graph Analytics & Network Analysis

• Design and implement graph-based models to identify patterns, clusters, communities, and relationships within complex datasets.

• Apply network analysis techniques using metrics such as clustering coefficient, degree assortativity, density, Gini index, and small-world index.

• Perform multi-hop network traversals and community detection using algorithms such as Louvain partitioning and similar graph clustering approaches.

• Build and query graph databases (Neo4j, ArangoDB) using Cypher Query Language to extract structural insights from connected data.

• Leverage GPU-accelerated graph libraries (cuGraph) to scale graph computations across large datasets efficiently.

Data Engineering & Pipeline Development

• Conduct thorough Exploratory Data Analysis (EDA) on large-scale structured and semi-structured datasets to surface quality issues, distributions, and key features.

• Build, optimize, and maintain scalable data pipelines and stored procedures across cloud data platforms such as BigQuery, PostgreSQL, or Hive.

• Automate data workflows using orchestration tools such as Apache Airflow or Kubeflow Pipelines.

• Apply GPU-accelerated computing (CUDA, CuPy, cuDF) to optimize processing performance on high-volume data workloads.

• Ensure data integrity, reproducibility, and documentation across all analytical workflows.

Statistical Modeling & Insight Generation

• Apply statistical modeling techniques to detect behavioral anomalies, trends, and patterns within datasets.

• Use time series analysis to identify temporal patterns and changes in data over time.

• Translate analytical findings into clear, actionable insights for both technical and non-technical stakeholders.

• Build dashboards and reports using visualization tools (e.g., Trino Superset) to communicate results effectively.

Collaboration & Documentation

• Work closely with product, engineering, and business teams to understand requirements and deliver relevant analytical solutions.

• Contribute to internal knowledge sharing through workshops, documentation, and peer reviews.

• Maintain well-documented codebases and analytical frameworks for long-term maintainability.

Required Skills & Qualifications

Must-Have

• 3+ years of experience in a Data Science, Data Analytics, or Graph Analytics role.

• Strong proficiency in Python with hands-on experience using NumPy, Pandas, CuPy, and cuDF.

• Practical experience with graph analytics libraries — NetworkX, cuGraph, Neo4j, or ArangoDB.

• Solid understanding of graph theory concepts: community detection, network metrics, graph traversal, and clustering algorithms.

• Proficiency in SQL; experience with BigQuery, PostgreSQL, MS SQL, Hive, or similar databases.

• Experience with GPU-based computing using CUDA for performance-critical data tasks.

• Strong analytical thinking and ability to work independently on ambiguous, open-ended problems.

Good to Have

• Experience with Cypher Query Language for querying graph databases (Neo4j / ArangoDB).

• Familiarity with graph ML frameworks such as PyTorch Geometric.

• Exposure to workflow orchestration tools — Apache Airflow or Kubeflow Pipelines.

• Knowledge of cloud data tools such as Trino, MinIO, or IBM Datastage.

• Basic scripting skills in Bash or C++ for automation or performance tasks.

• Experience presenting data insights to senior stakeholders or cross-functional teams.

• Research publications, patents, or open-source contributions in graph analytics or data science are a strong plus.

What We Offer

• Opportunity to solve high-impact, large-scale data problems using modern graph and analytics tools.

• Exposure to cutting-edge technologies including GPU-accelerated computing and graph ML.

• Collaborative, intellectually stimulating work environment with a strong engineering culture.

• Competitive compensation with performance-based incentives.

• Learning & development support — certifications, courses, and conference participation.

• Centrally located Pune office with a structured, in-person team culture.

Job Description – Data Scientist (Machine Learning & Forecasting)

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions.

The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact.

Key Responsibilities

• Design, develop, and deploy Machine Learning models for business-critical use cases.
• Build and optimize traditional ML models such as:
• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• Gradient Boosting (XGBoost, LightGBM, CatBoost)
• Support Vector Machines
• Clustering Algorithms
• Develop forecasting solutions using:
• ARIMA / SARIMA
• Prophet
• Exponential Smoothing
• Time-Series Regression Models
• Perform exploratory data analysis (EDA), feature engineering, and data validation.
• Evaluate model performance using appropriate statistical and business metrics.
• Work with structured and semi-structured datasets from multiple sources.
• Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
• Build scalable data pipelines and support model deployment in production environments.
• Monitor model performance, identify data drift, and implement model retraining strategies.
• Present insights and recommendations to technical and non-technical stakeholders.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
• 5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting.

Technical Skills

   Machine Learning

• Strong understanding of supervised and unsupervised learning algorithms.
• Experience with ensemble methods and advanced ML techniques.
• Expertise in model selection, hyperparameter tuning, and performance optimization.

Forecasting & Statistics

• Strong understanding of:
• Time-Series Analysis
• Forecasting Techniques
• Statistical Inference
• Hypothesis Testing
• Probability Distributions
• A/B Testing

Programming

• Advanced proficiency in Python.
• Experience with:
• Pandas
• NumPy
• Scikit-learn
• Statsmodels
• XGBoost / LightGBM
• Prophet

Data & SQL

• Strong SQL skills with experience in complex queries and performance optimization.
• Experience working with large-scale datasets.

Visualization

• Experience with Power BI, Tableau, Matplotlib, Seaborn, or Plotly.
• Cloud & MLOps (Preferred)
• Exposure to AWS, Azure, or GCP.
• Understanding of Docker, Kubernetes, CI/CD, and ML model deployment practices.

Key Competencies

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently in a fast-paced environment.
• Strong business acumen and data-driven decision-making mindset. 

Exp - 6-8.5 Yrs

Level - Assistant Manager

Skill - AI ML/Gen AI Engineer

Location - Hyderabad/ Bangalore / Gurgaon

Key Skills - GitHub Copilot and Gemini; AI/ML and Generative AI (GenAI); LLMs and GenAI agents/assistants (e.g., LangChain); cloud integration; and Python/R workflows

Key Qualifications:

§ A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor.

§ Strong software engineering foundation with deep understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices etc.

§ 5+ years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc.

§ Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc.

§ Proven experience with big data technologies, Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang, SQL/NoSQL.

§ Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP.

§ Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc.

§ Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

About the Internship

Nexora Group is seeking motivated and analytical students who are passionate about Data Science, Artificial Intelligence, and Machine Learning. This internship offers hands-on experience working with real-world datasets, AI-driven technologies, predictive analytics, and data visualization techniques.

Interns will gain practical exposure to data analysis workflows, AI-powered solutions, and industry-oriented projects while developing skills that are highly valued in today's technology landscape. Nexora Group focuses on innovation and technology-driven solutions across AI, digital experiences, and emerging technologies.

Key Responsibilities

• Collect, clean, and analyze structured and unstructured datasets.
• Perform Exploratory Data Analysis (EDA) to identify trends and patterns.
• Develop and evaluate Machine Learning models.
• Work with AI and Generative AI tools for data-driven solutions.
• Create dashboards, reports, and visualizations.
• Assist in predictive analytics and business intelligence projects.
• Document findings and present insights to mentors.
• Collaborate with team members on real-world projects.

Required Skills

• Basic knowledge of Python programming.
• Understanding of Data Science and Machine Learning concepts.
• Familiarity with Pandas, NumPy, and data visualization libraries.
• Basic understanding of statistics and data analysis.
• Knowledge of SQL is a plus.
• Strong analytical and problem-solving abilities.
• Passion for Artificial Intelligence and emerging technologies.

Eligibility

• B.Tech, BCA, MCA, B.Sc., M.Sc., or related disciplines.
• Students pursuing Data Science, Computer Science, AI, IT, Mathematics, Statistics, or related fields.
• Freshers and recent graduates are encouraged to apply.

What You Will Learn

✅ Data Analysis & Visualization

✅ Machine Learning Fundamentals

✅ Artificial Intelligence Applications

✅ Generative AI Tools & Techniques

✅ Predictive Analytics

✅ Business Intelligence Concepts

✅ Industry-Oriented Project Development

Benefits

✅ Internship Completion Certificate

✅ Letter of Recommendation (Performance-Based)

✅ Hands-on Industry Project Experience

✅ Professional Mentorship & Guidance

✅ Resume & LinkedIn Profile Enhancement

✅ Portfolio Development Support

✅ Exposure to AI & Data-Driven Technologies

Description:

-> Work on full-stack development projects, handling both front-end and back-end development tasks.

-> Gain practical experience in designing, developing and deploying scalable web and application solutions.

-> Collaborate with teams to build efficient, secure, and user-friendly applications using modern technologies.

-> Work with a wide range of technologies and domains, including:

  Java Application Programming

  Web Development

  Python Application Programming with Django

  Machine Learning

  Data Science

  Artificial Intelligence

  Cyber Security

  Data Analytics

-> Develop problem-solving, analytical, and technical skills by working on projects.

Duration: 1 - 6 months

Mode: Online/Offline

Eligibility: Any BCA/MCA pursuing Students can apply.

Perks:

-> Internship Certificate

-> Letter of Recommendation.

Description:

-> Work on full-stack development projects, handling both front-end and back-end development tasks.

-> Gain practical experience in designing, developing and deploying scalable web and application solutions.

-> Collaborate with teams to build efficient, secure, and user-friendly applications using modern technologies.

-> Work with a wide range of technologies and domains, including:

  Java Application Programming

  Web Development

  Python Application Programming with Django

  Machine Learning

  Data Science

  Artificial Intelligence

  Cyber Security

  Data Analytics

-> Develop problem-solving, analytical, and technical skills by working on projects.

Duration: 1 - 6 months

Mode: Online/Offline

Eligibility: Any BE/BTech pursuing Students can apply.

Perks:

-> Internship Certificate

-> Letter of Recommendation.

Strong Data Scientist / AI Engineer / Machine Learning Engineer profiles.

Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

We're Hiring | AI/ML Engineer (Training & Development) – Female Candidate Preferred

We are looking for a passionate and skilled Female AI/ML Engineer who can conduct engaging training sessions while also contributing to AI/ML development projects. The ideal candidate should have strong technical expertise along with excellent communication and presentation skills.

Experience: 2–3 Years

Key Skills: Python, Machine Learning, Deep Learning, Generative AI, LLMs, NLP, Computer Vision, LangChain, RAG, Prompt Engineering, TensorFlow, PyTorch, Scikit-learn

Training Expertise: Ability to deliver training sessions on AI/ML, Data Science, Python, Generative AI, and emerging technologies using various AI tools and platforms.

Preferred: Candidates with experience in both training and development activities.

📍 Location: Jaipur (On-site)

💻 Laptop Provided by Company

📅 Working Days: Monday to Saturday

💰 Salary: ₹25,000 – ₹30,000 per month

Strong Data Scientist / AI Engineer / Machine Learning Engineer profiles.

Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support.

Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.

Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.

Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

Position Title: Data Science Trainer

Company: TeksAcademy

Location: Hyderabad

Employment Type: Full-Time (Onsite)

About the Role:

We’re looking for an experienced and passionate Data Science Trainer to lead learning initiatives, impart industry-relevant knowledge, and build foundational and advanced skills in data science for our learners. As a Data Science Trainer, you’ll guide individuals or groups through the concepts and techniques needed to succeed in data analysis, machine learning, and data-driven decision-making.

Key Responsibilities:

• Conduct Data Science Training: Lead both online and in-person training sessions on a variety of data science topics such as statistics, programming (Python, R), machine learning, data visualization, and more.
• Create and Curate Course Materials: Develop and update educational resources, such as slides, tutorials, exercises, and datasets, ensuring they align with the latest industry standards.
• Facilitate Hands-On Learning: Engage learners with practical coding exercises and real-world problem-solving tasks to enhance their understanding of data science techniques.
• Assess and Provide Feedback: Evaluate students' progress through assessments, quizzes, and projects, giving personalized feedback to help them improve their skills.
• Stay Current with Trends: Continuously learn about emerging trends, tools, and techniques in data science, integrating these into training materials and courses.
• Provide Mentorship: Offer mentorship to students, helping them build confidence in applying data science concepts, troubleshooting issues, and building portfolios of their work.
• Collaborate and Improve: Work closely with other instructors, curriculum designers, and teams to improve and refine training programs, based on feedback and results.

Required Qualifications:

• Educational Background: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Experience: Demonstrated experience in data science, machine learning, statistical analysis, and working with data programming languages such as Python, R, and SQL.
• Teaching Experience: Proven track record of teaching or training in a technical field, especially data science, either online or in-person.
• Technical Expertise: Strong hands-on experience with data science tools and libraries like Pandas, NumPy, Scikit-learn, Matplotlib, Tensor Flow, etc.

About Us: Website: https://www.tundratechnical.ca/ & https://tundramanagedsolutions.com/

Experience: 5-8 years

Shift: EST

Location: Bangalore

Mode: Hybrid

Position Requirements

Core (Must-Have) Skills

• Proficiency in Python with advanced use of NumPy, Pandas, and Scikit-learn

• Expertise in SQL, including complex queries and performance optimization

• Strong foundation in machine learning techniques (regression, classification, clustering, ensemble methods)

• Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI

• MLOps practices (MLFlow, Kubeflow, CI/CD pipelines for ML workflows)

• Experience in data visualization (Seaborn, Plotly, Tableau, or Power BI)

• Applied knowledge of statistics and probability for model development

• Hands-on experience with cloud-based ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI)

• Exposure to large-scale data processing (Spark, Hadoop)

Preferred Skills

• Deep learning frameworks (TensorFlow, PyTorch)

• Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI

• MLOps practices (MLFlow, Kubeflow, CI/CD pipelines for ML workflows)

• Data pipeline orchestration (Airflow, Prefect)

• Business domain knowledge (e.g., retail, finance)

Key Activities

• Preparing and preprocessing structured and unstructured data for analysis

• Designing, training, and validating machine learning models

• Deploying and operationalizing models in collaboration with engineering teams

• Building dashboards and data-driven visual insights for stakeholders

• Partnering with product and engineering teams to align models with business needs

• Monitoring, optimizing, and retraining models for performance improvements

About the Role

We are looking for an analytical and detail-oriented Data Scientist with deep expertise in graph analytics, network analysis, and scalable data engineering. This is not a conventional machine learning role — the focus is on understanding complex relationships, structures, and patterns within large-scale datasets using graph-based methods and statistical modeling. You will work in a collaborative, fast-paced environment and be expected to contribute across the full data lifecycle — from raw data exploration through to production-grade analytical systems.

This is a full-time, in-office role based out of our Pune office (5 days a week).

Key Responsibilities

Graph Analytics & Network Analysis

• Design and implement graph-based models to identify patterns, clusters, communities, and relationships within complex datasets.

• Apply network analysis techniques using metrics such as clustering coefficient, degree assortativity, density, Gini index, and small-world index.

• Perform multi-hop network traversals and community detection using algorithms such as Louvain partitioning and similar graph clustering approaches.

• Build and query graph databases (Neo4j, ArangoDB) using Cypher Query Language to extract structural insights from connected data.

• Leverage GPU-accelerated graph libraries (cuGraph) to scale graph computations across large datasets efficiently.

Data Engineering & Pipeline Development

• Conduct thorough Exploratory Data Analysis (EDA) on large-scale structured and semi-structured datasets to surface quality issues, distributions, and key features.

• Build, optimize, and maintain scalable data pipelines and stored procedures across cloud data platforms such as BigQuery, PostgreSQL, or Hive.

• Automate data workflows using orchestration tools such as Apache Airflow or Kubeflow Pipelines.

• Apply GPU-accelerated computing (CUDA, CuPy, cuDF) to optimize processing performance on high-volume data workloads.

• Ensure data integrity, reproducibility, and documentation across all analytical workflows.

Statistical Modeling & Insight Generation

• Apply statistical modeling techniques to detect behavioral anomalies, trends, and patterns within datasets.

• Use time series analysis to identify temporal patterns and changes in data over time.

• Translate analytical findings into clear, actionable insights for both technical and non-technical stakeholders.

• Build dashboards and reports using visualization tools (e.g., Trino Superset) to communicate results effectively.

Collaboration & Documentation

• Work closely with product, engineering, and business teams to understand requirements and deliver relevant analytical solutions.

• Contribute to internal knowledge sharing through workshops, documentation, and peer reviews.

• Maintain well-documented codebases and analytical frameworks for long-term maintainability.

Required Skills & Qualifications

Must-Have

• 3+ years of experience in a Data Science, Data Analytics, or Graph Analytics role.

• Strong proficiency in Python with hands-on experience using NumPy, Pandas, CuPy, and cuDF.

• Practical experience with graph analytics libraries — NetworkX, cuGraph, Neo4j, or ArangoDB.

• Solid understanding of graph theory concepts: community detection, network metrics, graph traversal, and clustering algorithms.

• Proficiency in SQL; experience with BigQuery, PostgreSQL, MS SQL, Hive, or similar databases.

• Experience with GPU-based computing using CUDA for performance-critical data tasks.

• Strong analytical thinking and ability to work independently on ambiguous, open-ended problems.

Good to Have

• Experience with Cypher Query Language for querying graph databases (Neo4j / ArangoDB).

• Familiarity with graph ML frameworks such as PyTorch Geometric.

• Exposure to workflow orchestration tools — Apache Airflow or Kubeflow Pipelines.

• Knowledge of cloud data tools such as Trino, MinIO, or IBM Datastage.

• Basic scripting skills in Bash or C++ for automation or performance tasks.

• Experience presenting data insights to senior stakeholders or cross-functional teams.

• Research publications, patents, or open-source contributions in graph analytics or data science are a strong plus.

What We Offer

• Opportunity to solve high-impact, large-scale data problems using modern graph and analytics tools.

• Exposure to cutting-edge technologies including GPU-accelerated computing and graph ML.

• Collaborative, intellectually stimulating work environment with a strong engineering culture.

• Competitive compensation with performance-based incentives.

• Learning & development support — certifications, courses, and conference participation.

• Centrally located Pune office with a structured, in-person team culture.

About SkillSecureX

SkillSecureX is a technology-focused platform dedicated to providing practical learning opportunities and industry-oriented exposure in Data Science, Artificial Intelligence, Machine Learning, Web Development, and emerging technologies. Our goal is to help students and freshers gain real-world experience through project-based internships and hands-on learning.

About the Internship

We are looking for enthusiastic and motivated candidates for the role of Data Science with AI Intern. This internship is designed for students, freshers, and aspiring data professionals who want to build practical skills in Data Science, Artificial Intelligence, data analysis, and machine learning technologies.

Interns will work on real-world datasets, AI-based projects, and practical assignments while learning industry-relevant tools and workflows under mentorship.

Roles & Responsibilities

• Work on data collection, cleaning, and preprocessing

• Analyze datasets and generate meaningful insights

• Assist in developing AI and Machine Learning models

• Create reports, dashboards, and data visualizations

• Work with Python libraries and data science tools

• Participate in project discussions and team collaboration

• Support research and development activities related to AI solutions

Required Skills

• Basic understanding of Python programming

• Interest in Data Science and Artificial Intelligence

• Familiarity with Excel, statistics, or data analysis concepts is a plus

• Knowledge of Machine Learning basics is beneficial

• Strong analytical and problem-solving skills

• Willingness to learn and work on practical projects

Eligibility

• Students pursuing graduation or post-graduation

• Freshers interested in Data Science and AI

• Candidates looking to gain practical industry experience

Perks & Benefits

• Internship Completion Certificate

• Hands-on experience on practical projects

• Flexible remote working environment

• Mentorship and industry-oriented learning

• Opportunity to strengthen resume and technical skills

About the Internship

The Nexora Group is looking for motivated and enthusiastic interns for the role of Data Science with AI Intern. This internship provides practical exposure to data analysis, machine learning, AI tools, and real-world datasets through guided mentorship and project-based learning.

Interns will gain hands-on experience working on live tasks related to data processing, visualization, predictive analytics, and AI-driven solutions.

Responsibilities

• Assist in collecting, cleaning, and analyzing datasets.
• Work on data visualization and reporting tasks.
• Support machine learning and AI model development activities.
• Participate in research and implementation of AI-based solutions.
• Perform data preprocessing and feature engineering tasks.
• Collaborate with mentors and team members on project assignments.
• Test, evaluate, and improve model performance.
• Maintain project documentation and reports.

Required Skills

• Basic understanding of Python or any programming language.
• Interest in Data Science, Analytics, and AI technologies.
• Knowledge of statistics, data handling, or logical reasoning is a plus.
• Good analytical and problem-solving skills.
• Ability to learn and work collaboratively in a team environment.

Preferred Skills (Optional)

• Familiarity with Python libraries such as Pandas, NumPy, or Matplotlib.
• Basic understanding of Machine Learning concepts.
• Knowledge of SQL, Excel, or data visualization tools.
• Interest in Artificial Intelligence and automation technologies.

Who Can Apply

• Students pursuing B.Tech, BCA, MCA, B.Sc IT, M.Tech, or related fields.
• Freshers seeking practical exposure in Data Science and AI.
• Candidates passionate about analytics, AI, and emerging technologies.

Perks & Benefits

• Hands-on experience with real-world datasets and projects.
• Mentorship from experienced professionals.
• Internship Completion Certificate.
• Letter of Recommendation based on performance.
• Flexible learning and working environment.
• Opportunity to build practical technical skills.
• Top performers may receive future opportunities based on project requirements.

JOB DETAILS:

- Job Title: Lead I - Data Science - Python, Machine Learning, Spark 

- Industry: Global Digital Transformation Solutions Provider

- Experience: 5-10 years

- Job Location: Pune

- CTC Range: Best in Industry

JD for Data Scientist

Hands-on experience with data analysis tools:

Proficient in using tools such as Python and R for data manipulation, querying, and analysis.

Skilled in utilizing libraries like Pandas, NumPy, and Scikit-Learn to perform in-depth data analysis and modeling.

Skilled in machine learning and predictive analytics:

Expertise in building, training, and deploying machine learning models using frameworks such as TensorFlow and PyTorch.

Capable of performing tasks like regression, classification, clustering, and recommendation, leading to data-driven predictions and insights.

Expertise in big data technologies:

Proficient in handling large datasets using big data tools such as Spark.

Skilled in employing distributed computing and parallel processing techniques to ensure efficient data processing, storage, and analysis, enabling enterprise-level solutions and informed decision-making

Skills: Python, SQL, Machine Learning, and Deep Learning, with mandatory expertise in Generative AI.

Must-Haves

5–9 years of relevant experience in Python, SQL, Machine Learning, and Deep Learning, with mandatory expertise in Generative AI

******

NP - Immediate joiners only

Location-Pune 

Title: AI Solutions Architect

Location: Gurgaon

Experience: 2-6 years

Type: Full-Time

About the company:

InteligenAI is a fast growing, profitable AI product studio with a global clientele.

We design and deliver enterprise-grade, custom AI solutions that solve real problems - going far beyond makeshift PoCs and over-promising demos.

We’re building one of the most trusted AI services companies in the world - and are looking for a driven, entrepreneurial person to help us get there. Our work spans Agentic AI architectures, document digitization pipelines, retrieval-augmented generation (RAG) systems, and SFT + RLHF workflows - all built in-house so we can move fast, think deep and deliver with confidence.

If you are looking for meaningful work, high ownership and the freedom to push boundaries, you will feel right at home here.

About the role:

We are looking for a hands-on AI engineer to lead AI solution delivery across our client engagements. This role blends technical leadership with solution architecture and a strong product mindset. You will be at the frontline of AI solution delivery, where you will drive the full product lifecycle from understanding business objectives, designing technical approaches, building POCs to delivering production-grade AI systems.

This is not a backseat, “wait for instructions” role. You will work directly with founders, clients, and our growing AI team to shape solutions that make an impact. This role is ideal for someone with an entrepreneurial mindset, a desire to learn and grow constantly and someone who enjoys their work thoroughly. You will be handling multiple responsibilities simultaneously where you will be challenged every day. If you are looking for a 9-to-5 role, this may not be the right fit.

Key responsibilities:

·      Understand business problems, translate them into solution architectures and lead end-to-end AI solution delivery

·      Design and deliver production-grade ML/GenAI systems tailored to real-world use cases

·      Collaborate with clients to identify needs, present solutions and guide implementation

·      Act as a thought partner to the founder and contribute to strategic decisions

·      Lead and mentor a growing AI/Tech team

·      Collaborate with product and design teams to ship AI-driven features that solve real user problems

·      Continuously explore and experiment with cutting-edge GenAI tools, technologies and frameworks

Must have skills:

·      2+ years of hands-on experience building AI/ML solutions across domains

·      Proven ability to understand business workflows and design relevant AI solutions

·      Strong knowledge of GenAI and experience building scalable applications using LLMs, prompt engineering and embedding models

·      Proficient in Python and familiar with libraries/frameworks such as LangChain, Hugging Face Transformers, OpenAI APIs, Pinecone/FAISS

·      Solid understanding of data pipelines, data analytics and ability to take solutions from prototype to production

·      Self-starter mindset- ability to independently manage projects, make decisions and deliver outcomes from day 1

·      Excellent communication and problem-solving skills

Good to have:

·      Open-source contributions or personal GenAI projects

·      Experience working in startups or fast-paced, tech-first organizations

·      Experience with MLOps tools

·      Entrepreneurial experience

Job Title: Data Intern

Company: Honeybee Digital

Location: Remote

Internship Duration: 3 Months

Job Type: Internship

Working Hours

• Full-time: 9:00 AM – 6:00 PM
• Part-time: 9:00 AM – 1:00 PM / 1:00 PM – 6:00 PM

About the Role

We are looking for a detail-oriented and analytical Data Intern who is eager to work with data and gain hands-on experience in data management, analysis, and reporting. This role is ideal for candidates interested in building a career in data analysis, business intelligence, or data science.

Key Responsibilities

• Collect, organize, and maintain data from various sources
• Clean and preprocess data to ensure accuracy and consistency
• Assist in data analysis and generate basic insights
• Create reports and dashboards using tools like Excel or Google Sheets
• Support teams with data requirements for marketing, operations, and business decisions
• Perform data entry and validation tasks
• Identify patterns, trends, and anomalies in datasets
• Maintain proper documentation of data processes

Requirements

• Basic knowledge of Excel / Google Sheets
• Understanding of data handling and analysis concepts
• Attention to detail and accuracy
• Basic problem-solving and analytical thinking skills
• Familiarity with tools like Python, SQL (optional but preferred)
• Ability to manage tasks and meet deadlines
• Willingness to learn and work with data

Skills You Will Gain

• Hands-on experience in data collection, cleaning, and analysis
• Exposure to real-world datasets and reporting
• Practical knowledge of Excel, data visualization, and analytics tools
• Understanding of business decision-making using data
• Experience working in a professional environment

Who Can Apply

• Students pursuing Data Science, Computer Science, IT, Statistics, or related fields
• Freshers interested in data analysis and data-related roles
• Candidates looking to gain practical experience in data handling and analytics

About the Role

We are looking for a passionate AI/ML Software Engineer to join our product team and help build intelligent, scalable, and production-ready machine learning solutions. You will work closely with product managers, designers, and backend engineers to integrate AI capabilities into core product features and drive data-driven innovation.

Key Responsibilities

• Design, develop, and deploy machine learning models into production environments
• Build and maintain scalable ML pipelines for data processing, training, and inference
• Collaborate with cross-functional teams to identify AI-driven product opportunities
• Translate business requirements into ML solutions and technical implementations
• Optimize model performance, accuracy, and latency for real-time applications
• Integrate AI/ML models with APIs and backend systems
• Monitor model performance and implement continuous improvement strategies
• Ensure best practices in data handling, model versioning, and reproducibility
• Stay updated with the latest advancements in AI/ML and apply them to product innovation

Required Skills & Qualifications

• Bachelor’s engineering degree in Computer Science, AI, Data Science, or related field
• Strong programming skills in Python (experience with Java/Go is a plus)
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Solid understanding of machine learning algorithms and statistical concepts
• Experience in building and deploying ML models in production
• Familiarity with REST APIs, microservices architecture, and cloud platforms (AWS/GCP/Azure)
• Experience with data processing tools (Pandas, NumPy, Spark, etc.)
• Knowledge of version control systems like Git 

What you’ll do?

Partnering with internal business owners (product, marketing, edit, etc.) to understand needs anddevelop custom analysis to optimize for user engagement and retention.

Good understanding of the underlying business and workings of cross functional teams for successful execution.

Design and develop analyses based on business requirement needs and challenges.

Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.

Providing statistical analysis on custom research projects and consult on A/B testing and otherstatistical analysis as needed.

Other reports and custom analysis as required.

Identify and use appropriate investigative and analytical technologies to interpret and verify results.

Apply and learn a wide variety of tools and languages to achieve results.

Use best practices to develop statistical and/ or machine learning techniques to build models thataddress business needs.

Collaborate with the team in order to improve the effectiveness of business decisions throughthe use of data and machine learning/predictive modeling.

Innovate on projects by using new modeling techniques or tools.

Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept. C

ommunicate findings to team and leadership to ensure models are well understood and incorporated into business processes.

Who you need to be?

Typically has 2 - 6 years of relevant experience.

Preferred education: Bachelor's degree in a technical field or equivalent experience Experience in advanced analytics, model building, statistical modeling, optimization, and machinelearning algorithms.

Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection.

Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.

Strong with programming languages like Python and data processing using SQL or equivalent andability to experiment with newer open-source tools.

Experience in normalizing data to ensure it is homogeneous and consistently formatted to enablesorting, query and analysis.

Experience designing, developing, implementing and maintaining a database and programs tomanage data analysis efforts.

Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE)

Experience in risk and credit score domains preferred.

Job location  Chennai/Bangalore (work from office-Hybrid)

🤖 Data Scientist – Frontier AI for Data Platforms & Distributed Systems (4–8 Years)

Experience: 4–8 Years

Location: Bengaluru (On-site / Hybrid)

Company: Publicly Listed, Global Product Platform

🧠 About the Mission

We are building a Top 1% AI-Native Engineering & Data Organization — from first principles.

This is not incremental improvement.

This is a full-stack transformation of a large-scale enterprise into an AI-native data platform company.

We are re-architecting:

• Legacy systems → AI-native architectures
• Static pipelines → autonomous, self-healing systems
• Data platforms → intelligent, learning systems
• Software workflows → agentic execution layers

This is the kind of shift you would expect from companies like Google or Microsoft —

Except here, you will build it from day zero and scale it globally.

🧠 The Opportunity: This role sits at the intersection of three high-impact domains:

1. Frontier AI Systems: Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI

2. Data Platforms: Warehouses, Lakehouses, Streaming Systems, Query Engines

3. Distributed Systems: High-throughput, low-latency, multi-region infrastructure

We are building systems where:

• Data platforms optimize themselves using ML/LLMs
• Pipelines are autonomous, self-healing, and adaptive
• Queries are generated, optimized, and executed intelligently
• Infrastructure learns from usage and evolves continuously

This is: AI as the control plane for data infrastructure

🧩 What You’ll Work On

You will design and build AI-native systems deeply embedded inside data infrastructure.

1. AI-Native Data Platforms

• Build LLM-powered interfaces:
• Natural language → SQL / pipelines / transformations
• Design semantic data layers:
• Embeddings, vector search, knowledge graphs
• Develop AI copilots:
• For data engineers, analysts, and platform users

2. Autonomous Data Pipelines

• Build self-healing ETL/ELT systems using AI agents
• Create pipelines that:
• Detect anomalies in real time
• Automatically debug failures
• Dynamically optimize transformations

3. Intelligent Query & Compute Optimization

• Apply ML/LLMs to:
• Query planning and execution
• Cost-based optimization using learned models
• Workload prediction and scheduling
• Build systems that:
• Learn from query patterns
• Continuously improve performance and cost efficiency

4. Distributed Data + AI Infrastructure

• Architect systems operating at:
• Billions of events per day
• Petabyte-scale data
• Work with:
• Distributed compute engines (Spark / Flink / Ray class systems)
• Streaming systems (Kafka-class infra)
• Vector databases and hybrid retrieval systems

5. Learning Systems & Feedback Loops

• Build closed-loop AI systems:
• Execution → feedback → model updates
• Develop:
• Continual learning pipelines
• Online learning systems for infra optimization
• Experimentation frameworks (A/B, bandits, eval pipelines)

6. LLM & Agentic Systems (Infra-Aware)

• Build agents that understand data systems
• Enable:
• Autonomous pipeline debugging
• Root cause analysis for infra failures
• Intelligent orchestration of data workflows

🧠 What We’re Looking For

Core Foundations

• Strong grounding in:
• Machine Learning, Deep Learning, NLP
• Statistics, optimization, probabilistic systems
• Distributed systems fundamentals
• Deep understanding of:
• Transformer architectures
• Modern LLM ecosystems

Hands-On Expertise

• Experience building:
• LLM / GenAI systems (RAG, fine-tuning, embeddings)
• Data platforms (warehouse, lake, lakehouse architectures)
• Distributed pipelines and compute systems
• Strong programming skills:
• Python (ML/AI stack)
• SQL (deep understanding — query planning, optimization mindset)

Systems Thinking (Critical)

You think in systems, not components.

• Built or worked on:
• Large-scale data pipelines
• High-throughput distributed systems
• Low-latency, high-concurrency architectures
• Understand:
• Query optimization and execution
• Data partitioning, indexing, caching
• Trade-offs in distributed systems

🔥 What Sets You Apart (Top 1%)

• Built AI-powered data platforms or infra systems in production
• Designed or contributed to:
• Query engines / optimizers
• Data observability / lineage systems
• AI-driven infra or AIOps platforms
• Experience with:
• Multi-modal AI (logs, metrics, traces, text)
• Agentic AI systems
• Autonomous infrastructure
• Worked on systems at scale comparable to:
• Google (BigQuery-like systems)
• Meta (real-time analytics infra)
• Snowflake / Databricks (lakehouse architectures)

🧬 Ideal Background (Not Mandatory)

We often see strong candidates from:

• Data infrastructure or platform engineering teams
• AI-first startups or research-driven environments
• High-scale product companies

Experience building:

• Internal platforms used by 1000s of engineers
• Systems serving millions of users / high throughput workloads
• Multi-region, distributed cloud systems

🧠 The Kind of Problems You’ll Solve

• Can LLMs replace traditional query optimizers?
• How do we build self-healing data pipelines at scale?
• Can data systems learn from every query and improve automatically?
• How do we embed reasoning and planning into infrastructure layers?
• What does a fully autonomous data platform look like?

Background: We Commonly See (But Not Limited To)

Our team often includes engineers from top-tier institutions and strong research or product backgrounds, including:

• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

Job Title: Senior Data Scientist

Location: Pune

Job Type: Full-Time

About TVARIT

TVARIT GmbH specializes in developing and delivering cutting-edge artificial intelligence (AI) solutions for the metal industry, including steel, aluminum, copper, cast iron, and more. Our software products empower customers to make intelligent, data-driven decisions, driving advancements in Predictive Quality (PsQ), Predictive Maintenance (PdM), and Energy Consumption Reduction (PsE), etc.

With a strong portfolio of renowned reference customers, state-of-the-art technology, a talented research team from prestigious universities, and recognition through esteemed awards such as the EU Horizon 2020 AI Prize, TVARIT is recognized as one of the most innovative AI companies in Germany and Europe.

We are looking for a self-motivated person with a positive "can-do" attitude and excellent oral and written communication skills in English.

About the Role

We are looking for a highly skilled and motivated Senior Data Scientist who is passionate about solving complex data problems and developing cutting-edge solutions. This role requires someone with a strong technical background in data science, with full-stack development exposure from requirement gathering to solution deployment. The ideal candidate will be comfortable working as an individual contributor and as an active team member.

Key Responsibilities

· Translate business challenges into ML solutions by understanding customer needs and the broader context.

· Perform exploratory data analysis (EDA) and feature engineering on large-scale datasets.

· Write clean, efficient, and maintainable Python code for data processing, modeling, and analysis, following MLOps best practices.

· Build, optimize, deploy, and monitor scalable machine learning models and pipelines on cloud platforms (Azure preferred; AWS/GCP is a plus)

· Actively participate in code reviews, technical discussions, and knowledge-sharing sessions to drive innovation and best practices.

· Lead client discussions and present actionable insights and recommendations to stakeholders effectively.

· Mentor junior data scientists, providing guidance on model development, best practices, and technical problem-solving.

Qualifications

· Bachelor’s or master's degree in Metallurgy, mechanical, IT, Computer, or a related field from IIT, NIT, or top university.

· 4+ years of experience in data science and machine learning.

· Experience in the metal industry, manufacturing industry, or similar industry exposure

Technical Skills

· Strong Python programming skills with experience in libraries like Pandas, Scikit-learn, TensorFlow, or PyTorch.

· Strong foundation in ML & AI, covering statistical analysis, time series forecasting, deep learning, and optimization, with expertise in ML techniques like Random Forest, Gradient Boosting, Neural Networks, SVM, Clustering, PCA, Reinforcement Learning and and optimization algorithms.

· Proficiency in cloud platforms such as Azure [Preferred], AWS, or GCP.

· Good to have experience with real-time AI model deployment in industrial environments [On-premises, cloud or edge]

· Familiar with SQL and NoSQL databases.

· Understanding of MLOps, including model versioning, monitoring, and deployment.

· Good to have knowledge of deep learning architectures and techniques for computer vision, NLP, and generative AI is plus

· Strong analytical and problem-solving skills with a structured approach to debugging and optimization.

· Effective communicator and team collaborator in agile, fast-paced environments.

· Ability to work in a fast-paced, agile environment and adapt to changing priorities.

FULL STACK DEVELOPER

JOB DESCRIPTION – FULL STACK DEVELOPER 

Location: Bangalore 

Key Responsibilities:       

Establish processes, SLAs, and escalation protocols for the support & maintenance of web applications       

Manage stakeholders with effective communication & collaborate with cross functional teams to address issues and maintain business continuity.      

Design, implement, unit test, and build business applications using React, React-Native, .Net Core, .Net 8, Azure/AWS and leveraging an agile methodology and latest tech like Agentic AI & Gihub Copilot.     

Facilitate scrum ceremonies including sprint planning, retrospectives, reviews, and daily stand-ups·       

Facilitate discussion, assessment of alternatives or different approaches, decision making, and conflict resolution within the development team       

Develop and administer CI/CD pipelines in cloud-hosted Git repositories, and source control artifacts via Git in alignment with common branching strategies and workflows    

Assist Software Designer/Implementers with the creation of detailed software design specifications      

Participate in the system specification review process to ensure system requirements can be translated into valid software architecture       

Integrate internal and external product designs into a cohesive user experience       

Identify and keep track of metrics that indicate how software is performing     

Handle technical and non-technical queries from the development team and stakeholders      

Ensure that all development practices follow best practices and any relevant policies / procedures 

Other Duties·       Maintain project reporting including dashboards, status reports, road maps, burn down, velocity, and resource utilization.    

Own the technical solution and ensure all technical aspects are implemented as designed. ·       

Partner with the customer success team and aid in triaging and troubleshooting customer support issues spanning across a range of software components, infrastructure, integrations, and services, some of which target 24/7/365 availability     

Flexible to work in rotational shift   

Required Qualification     

Previous experience of leading full stack technology projects with scrum teams and stakeholder management·       

BTech or MTech in computer science, or related field·       

3-5 years of experience.  

Required Knowledge, Skills and Abilities: (Include any required computer skills, certifications, licenses, languages, etc)·      

With Proficiency in .NET Core/.Net 8/, React, React-Native, Redux, Material, Bootstrap, Typescript, SCSS, Microservices, EF, LINQ, SQL, Azure/AWS, CI CD, Agile, Agentic AI, Github Copilot·       

Azure Dev Ops, Design System, Micro front ends, Data Science·       

Stakeholder management & excellent communication skills.    

Must have skills

React - 3 years

React Native - 3 years

Redux - 1 years

Material UI - 1 years

Typescript - 1 years

Bootstrap - 1 years

Microservices - 2 years

SQL - 1 years

Azure - 1 years

Nice to have skills

.NET Core - 3 years

NET 8 - 3 years

AWS - 1 years

LINQ - 1 years

Description

We are currently hiring for the position of Data Scientist/ Senior Machine Learning Engineer (6–7 years’ experience).

Please find the detailed Job Description attached for your reference. We are looking for candidates with strong experience in:

• Machine Learning model development
• Scalable data pipeline development (ETL/ELT)
• Python and SQL
• Cloud platforms such as Azure/AWS/Databricks
• ML deployment environments (SageMaker, Azure ML, etc.)

Kindly note:

• Location: Pune (Work From Office)
• Immediate joiners preferred

While sharing profiles, please ensure the following details are included:

• Current CTC
• Expected CTC
• Notice Period
• Current Location
• Confirmation on Pune WFO comfort

Must have skills

Machine Learning - 6 years

Python - 6 years

ETL(Extract, Transform, Load) - 6 years

SQL - 6 years

Azure - 6 years

Description

JOB DESCRIPTION – SENIOR ANALYST – DATA SCIENTIST 

Key Responsibilities ·       

Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions·       

Advanced skills with statistical/programming in Python and data querying languages (e.g., SQL, Hadoop/Hive, Scala)·       

Solid understanding of time-series forecasting techniques·       

Good hands-on skills in both feature engineering and hyperparameter optimization·       

Able to write clean and tested code that can be maintained by other software engineers·       

Able to clearly summarize and communicate data analysis assumptions and results·       

Able to craft effective data pipelines to transform your analyses from offline to production systems·       

Self-motivated and a proactive problem solver who can work independently and in teams·       

Connects both externally and internally to understand industry trends, technology advances and outstanding processes or solutions·       

Is collaborative and engages (strategic & tactical. Able to influence without authority, handle complex issues and implement positive change·       

Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science·       

Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment ·       

Provide guidance and leadership to more junior data scientists, managing processes and flow of work, vetting designs, and mentoring team members to realize their full potential·       

Lead discussions at peer review and use interpersonal skills to positively influence decision making·       

Provide subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices·       

Facilitate cross-geography sharing of new ideas, learnings, and best-practices 

What We Are Looking For 

Required Qualifications ·       

Master's degree in a quantitative field such as Data Science, Statistics, Applied Mathematics or Bachelor's degree in engineering, computer science, or related field. ·       

4 – 6 years of total work experience as data scientist or analytical role, with at least 2-3 years of experience in time series forecasting·       

A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project ·       

Strong experience in Time Series Forecasting and Demand Planning ·       

Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) ·       

Good hands-on skills in both feature engineering and hyperparameter optimization ·       

Experience producing high-quality code, tests, documentation·       

Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies·       

Proficiency in statistical concepts and ML algorithms·       

Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team·       

Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results·       

Self-motivated and a proactive problem solver who can work independently and in teams·       

Outstanding verbal and written communication skills with the ability to effectively advocate technical solutions to engineering and business teams 

Desired Qualifications ·      

Experience working in one or multiple supply chain functions (e.g., procurement, planning, manufacturing, quality, logistics) is strongly preferred ·       

Experience in applying AI/ML within a CPG or Healthcare business environment is strongly preferred ·       

Experience in creating CI/CD pipelines for deployment using Jenkins. ·       

Experience implementing MLOPs framework along with understanding of data security·       

Implementation on ML models·       

Exposure to visualization packages and Azure tech stack.  

Must have skills

Python - 2 years

Data Science - 4 years

SQL - 2 years

Machine Learning - 2 years

Nice to have skills

Data Analysis - 4 years

Time Series Forecasting - 2 years

Demand Planning - 2 years

Hadoop - 2 years

Statistical concepts - 2 years

Supply chain functions - 2 years

Data Scientist or Senior Machine Learning Engineer

We are currently hiring for the position of Data Scientist/ Senior Machine Learning Engineer (6–7 years' experience).

Please find the detailed Job Description attached for your reference.

We are looking for candidates with strong experience in:

• Machine Learning model development
• Scalable data pipeline development (ETL/ELT)
• Python and SQL
• Cloud platforms such as Azure/AWS/Databricks
• ML deployment environments (SageMaker, Azure ML, etc.)

Kindly note:

• Location: Pune (Work from Office)
• Immediate joiners preferred

While sharing profiles, please ensure the following details are included:

• Current CTC
• Expected CTC
• Notice Period
• Current Location
• Confirmation on Pune WFO comfort

Must have Skills

• Machine Learning - 6 Years
• Python - 6 Years
• ETL (Extract, Transform, Load) - 6 Years
• SQL - 6 Years
• Azure - 6 Years

Request you to share relevant profiles at the earliest. Looking forward to your support.

Job Description:

As a Data Science Intern, you will collaborate with our data science and analytics teams to work on meaningful projects involving data analysis, predictive modeling, and statistical modeling. You will have the opportunity to apply your academic knowledge in a practical, fast-paced environment, contribute to key data-driven projects, and gain valuable experience with industry-leading tools and technologies.

Responsibilities:

• Assist in collecting, cleaning, and preprocessing data from various sources.
• Perform exploratory data analysis to identify trends, patterns, and anomalies.
• Develop and implement machine learning models and algorithms.
• Create data visualizations and reports to communicate findings to stakeholders.
• Collaborate with team members on data-driven projects and research.
• Participate in meetings and contribute to discussions on project progress and strategy.
• Work with large datasets to clean, preprocess, and analyze data.
• Build and deploy statistical and machine learning models to generate actionable insights.
• Conduct exploratory data analysis (EDA) to uncover trends, patterns, and correlations.
• Assist in the creation of data visualizations and dashboards for reporting insights.
• Support the development and improvement of data pipelines and algorithms.
• Collaborate with cross-functional teams to understand data needs and translate them into actionable analytics solutions.
• Contribute to the documentation and presentation of results, findings, and recommendations.
• Participate in team meetings, brainstorming sessions, and project discussions.

Duration: 03 Months (with the possibility of extending up to 6 months)

MODE: Work From Home (Online)

Requirements:

• Any Graduate / PassOuts / Freasher can apply.
• Currently pursuing a Bachelor's or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• Proficiency in programming languages such as Python, R, or SQL.
• Strong foundation in statistics, probability, and data analysis techniques.

Benefits

Internship Certificate

Letter of recommendation

Stipend Performance Based

Part time work from home (2-3 Hrs per day)

5 days a week, Fully Flexible Shift

JOB DETAILS:

* Job Title: Principal Data Scientist

* Industry: Healthcare

* Salary: Best in Industry

* Experience: 6-10 years

* Location: Bengaluru

Preferred Skills: Generative AI, NLP & ASR, Transformer Models, Cloud Deployment, MLOps

Criteria:

1. Candidate must have 7+ years of experience in ML, Generative AI, NLP, ASR, and LLMs (preferably healthcare).
2. Candidate must have strong Python skills with hands-on experience in PyTorch/TensorFlow and transformer model fine-tuning.
3. Candidate must have experience deploying scalable AI solutions on AWS/Azure/GCP with MLOps, Docker, and Kubernetes.
4. Candidate must have hands-on experience with LangChain, OpenAI APIs, vector databases, and RAG architectures.
5. Candidate must have experience integrating AI with EHR/EMR systems, ensuring HIPAA/HL7/FHIR compliance, and leading AI initiatives.

Job Description

Principal Data Scientist

(Healthcare AI | ASR | LLM | NLP | Cloud | Agentic AI)

Job Details

• Designation: Principal Data Scientist (Healthcare AI, ASR, LLM, NLP, Cloud, Agentic AI)
• Location: Hebbal Ring Road, Bengaluru
• Work Mode: Work from Office
• Shift: Day Shift
• Reporting To: SVP
• Compensation: Best in the industry (for suitable candidates)

Educational Qualifications

• Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
• Technical certifications in AI/ML, NLP, or Cloud Computing are an added advantage

Experience Required

• 7+ years of experience solving real-world problems using:
• Natural Language Processing (NLP)
• Automatic Speech Recognition (ASR)
• Large Language Models (LLMs)
• Machine Learning (ML)
• Preferably within the healthcare domain
• Experience in Agentic AI, cloud deployments, and fine-tuning transformer-based models is highly desirable

Role Overview

This position is part of company, a healthcare division of Focus Group specializing in medical coding and scribing.

We are building a suite of AI-powered, state-of-the-art web and mobile solutions designed to:

• Reduce administrative burden in EMR data entry
• Improve provider satisfaction and productivity
• Enhance quality of care and patient outcomes

Our solutions combine cutting-edge AI technologies with live scribing services to streamline clinical workflows and strengthen clinical decision-making.

The Principal Data Scientist will lead the design, development, and deployment of cognitive AI solutions, including advanced speech and text analytics for healthcare applications. The role demands deep expertise in generative AI, classical ML, deep learning, cloud deployments, and agentic AI frameworks.

Key Responsibilities

AI Strategy & Solution Development

• Define and develop AI-driven solutions for speech recognition, text processing, and conversational AI
• Research and implement transformer-based models (Whisper, LLaMA, GPT, T5, BERT, etc.) for speech-to-text, medical summarization, and clinical documentation
• Develop and integrate Agentic AI frameworks enabling multi-agent collaboration
• Design scalable, reusable, and production-ready AI frameworks for speech and text analytics

Model Development & Optimization

• Fine-tune, train, and optimize large-scale NLP and ASR models
• Develop and optimize ML algorithms for speech, text, and structured healthcare data
• Conduct rigorous testing and validation to ensure high clinical accuracy and performance
• Continuously evaluate and enhance model efficiency and reliability

Cloud & MLOps Implementation

• Architect and deploy AI models on AWS, Azure, or GCP
• Deploy and manage models using containerization, Kubernetes, and serverless architectures
• Design and implement robust MLOps strategies for lifecycle management

Integration & Compliance

• Ensure compliance with healthcare standards such as HIPAA, HL7, and FHIR
• Integrate AI systems with EHR/EMR platforms
• Implement ethical AI practices, regulatory compliance, and bias mitigation techniques

Collaboration & Leadership

• Work closely with business analysts, healthcare professionals, software engineers, and ML engineers
• Implement LangChain, OpenAI APIs, vector databases (Pinecone, FAISS, Weaviate), and RAG architectures
• Mentor and lead junior data scientists and engineers
• Contribute to AI research, publications, patents, and long-term AI strategy

Required Skills & Competencies

• Expertise in Machine Learning, Deep Learning, and Generative AI
• Strong Python programming skills
• Hands-on experience with PyTorch and TensorFlow
• Experience fine-tuning transformer-based LLMs (GPT, BERT, T5, LLaMA, etc.)
• Familiarity with ASR models (Whisper, Canary, wav2vec, DeepSpeech)
• Experience with text embeddings and vector databases
• Proficiency in cloud platforms (AWS, Azure, GCP)
• Experience with LangChain, OpenAI APIs, and RAG architectures
• Knowledge of agentic AI frameworks and reinforcement learning
• Familiarity with Docker, Kubernetes, and MLOps best practices
• Understanding of FHIR, HL7, HIPAA, and healthcare system integrations
• Strong communication, collaboration, and mentoring skills

Candidate must have 7+ years of experience in ML, Generative AI, NLP, ASR, and LLMs (preferably healthcare).

Candidate must have strong Python skills with hands-on experience in PyTorch/TensorFlow and transformer model fine-tuning.

Candidate must have experience deploying scalable AI solutions on AWS/Azure/GCP with MLOps, Docker, and Kubernetes.

Candidate must have hands-on experience with LangChain, OpenAI APIs, vector databases, and RAG architectures.

Candidate must have experience integrating AI with EHR/EMR systems, ensuring HIPAA/HL7/FHIR compliance, and leading AI initiatives.

Review Criteria:

• Strong Dremio / Lakehouse Data Architect profile
• 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
• Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
• Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
• Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
• Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
• Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
• Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
• Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies

Preferred:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments

Role & Responsibilities:

You will be responsible for architecting, implementing, and optimizing Dremio-based data lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

Ideal Candidate:

• Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

Preferred:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
• Exposure to Snowflake, Databricks, or BigQuery environments.
• Experience in high-tech, manufacturing, or enterprise data modernization programs.

Hi,

Greetings from Ampera!

we are looking for a Data Scientist with strong Python & Forecasting experience.

Title                               : Data Scientist – Python & Forecasting

Experience                   : 4 to 7 Yrs

Location                       : Chennai/Bengaluru

Type of hire                  : PWD and Non PWD

Employment Type     : Full Time

Notice Period             : Immediate Joiner

Working hours           : 09:00 a.m. to 06:00 p.m.

Workdays                   : Mon - Fri

Job Description:

We are looking for an experienced Data Scientist with strong expertise in Python programming and forecasting techniques. The ideal candidate should have hands-on experience building predictive and time-series forecasting models, working with large datasets, and deploying scalable solutions in production environments.

Key Responsibilities

• Develop and implement forecasting models (time-series and machine learning based).
• Perform exploratory data analysis (EDA), feature engineering, and model validation.
• Build, test, and optimize predictive models for business use cases such as demand forecasting, revenue prediction, trend analysis, etc.
• Design, train, validate, and optimize machine learning models for real-world business use cases.
• Apply appropriate ML algorithms based on business problems and data characteristics
• Write clean, modular, and production-ready Python code.
• Work extensively with Python Packages & libraries for data processing and modelling.
• Collaborate with Data Engineers and stakeholders to deploy models into production.
• Monitor model performance and improve accuracy through continuous tuning.
• Document methodologies, assumptions, and results clearly for business teams.

Technical Skills Required:

Programming

• Strong proficiency in Python
• Experience with Pandas, NumPy, Scikit-learn

Forecasting & Modelling

• Hands-on experience in Time Series Forecasting (ARIMA, SARIMA, Prophet, etc.)
• Experience with ML-based forecasting models (XGBoost, LightGBM, Random Forest, etc.)
• Understanding of seasonality, trend decomposition, and statistical modeling

Data & Deployment

• Experience handling structured and large datasets
• SQL proficiency
• Exposure to model deployment (API-based deployment preferred)
• Knowledge of MLOps concepts is an added advantage

Tools (Preferred)

• TensorFlow / PyTorch (optional)
• Airflow / MLflow
• Cloud platforms (AWS / Azure / GCP)

Educational Qualification

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or related field.

Key Competencies

• Strong analytical and problem-solving skills
• Ability to communicate insights to technical and non-technical stakeholders
• Experience working in agile or fast-paced environments

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

JOB DETAILS:

* Job Title: Lead II - Software Engineering - AWS, Apache Spark (PySpark/Scala), Apache Kafka

* Industry: Global digital transformation solutions provider

* Salary: Best in Industry

* Experience: 5-8 years

* Location: Hyderabad

Job Summary

We are seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms. The role involves working with large-scale batch and real-time data processing systems, collaborating with cross-functional teams, and ensuring data reliability, security, and performance across the data lifecycle.

Key Responsibilities

ETL Pipeline Development & Optimization

• Design, develop, and maintain complex end-to-end ETL pipelines for large-scale data ingestion and processing.
• Optimize data pipelines for performance, scalability, fault tolerance, and reliability.

Big Data Processing

• Develop and optimize batch and real-time data processing solutions using Apache Spark (PySpark/Scala) and Apache Kafka.
• Ensure fault-tolerant, scalable, and high-performance data processing systems.

Cloud Infrastructure Development

• Build and manage scalable, cloud-native data infrastructure on AWS.
• Design resilient and cost-efficient data pipelines adaptable to varying data volume and formats.

Real-Time & Batch Data Integration

• Enable seamless ingestion and processing of real-time streaming and batch data sources (e.g., AWS MSK).
• Ensure consistency, data quality, and a unified view across multiple data sources and formats.

Data Analysis & Insights

• Partner with business teams and data scientists to understand data requirements.
• Perform in-depth data analysis to identify trends, patterns, and anomalies.
• Deliver high-quality datasets and present actionable insights to stakeholders.

CI/CD & Automation

• Implement and maintain CI/CD pipelines using Jenkins or similar tools.
• Automate testing, deployment, and monitoring to ensure smooth production releases.

Data Security & Compliance

• Collaborate with security teams to ensure compliance with organizational and regulatory standards (e.g., GDPR, HIPAA).
• Implement data governance practices ensuring data integrity, security, and traceability.

Troubleshooting & Performance Tuning

• Identify and resolve performance bottlenecks in data pipelines.
• Apply best practices for monitoring, tuning, and optimizing data ingestion and storage.

Collaboration & Cross-Functional Work

• Work closely with engineers, data scientists, product managers, and business stakeholders.
• Participate in agile ceremonies, sprint planning, and architectural discussions.

Skills & Qualifications

Mandatory (Must-Have) Skills

1. AWS Expertise

• Hands-on experience with AWS Big Data services such as EMR, Managed Apache Airflow, Glue, S3, DMS, MSK, and EC2.
• Strong understanding of cloud-native data architectures.

1. Big Data Technologies

• Proficiency in PySpark or Scala Spark and SQL for large-scale data transformation and analysis.
• Experience with Apache Spark and Apache Kafka in production environments.

1. Data Frameworks

• Strong knowledge of Spark DataFrames and Datasets.

1. ETL Pipeline Development

• Proven experience in building scalable and reliable ETL pipelines for both batch and real-time data processing.

1. Database Modeling & Data Warehousing

• Expertise in designing scalable data models for OLAP and OLTP systems.

1. Data Analysis & Insights

• Ability to perform complex data analysis and extract actionable business insights.
• Strong analytical and problem-solving skills with a data-driven mindset.

1. CI/CD & Automation

• Basic to intermediate experience with CI/CD pipelines using Jenkins or similar tools.
• Familiarity with automated testing and deployment workflows.

Good-to-Have (Preferred) Skills

• Knowledge of Java for data processing applications.
• Experience with NoSQL databases (e.g., DynamoDB, Cassandra, MongoDB).
• Familiarity with data governance frameworks and compliance tooling.
• Experience with monitoring and observability tools such as AWS CloudWatch, Splunk, or Dynatrace.
• Exposure to cost optimization strategies for large-scale cloud data platforms.

Skills: big data, scala spark, apache spark, ETL pipeline development

******

Notice period - 0 to 15 days only

Job stability is mandatory

Location: Hyderabad

Note: If a candidate is a short joiner, based in Hyderabad, and fits within the approved budget, we will proceed with an offer

F2F Interview: 14th Feb 2026

3 days in office, Hybrid model.

Hi,

PFB the Job Description for Data Science with ML

Type of hire                  : PWD and Non PWD

Employment Type    : Full Time

Notice Period            : Immediate Joiner

Work Days                    : Mon - Fri

About Ampera:

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards

About the Role

We are looking for a skilled Data Scientist with strong Machine Learning experience to design, develop, and deploy data-driven solutions. The role involves working with large datasets, building predictive and ML models, and collaborating with cross-functional teams to translate business problems into analytical solutions.

Key Responsibilities

• Analyze large, structured and unstructured datasets to derive actionable insights.
• Design, build, validate, and deploy Machine Learning models for prediction, classification, recommendation, and optimization.
• Apply statistical analysis, feature engineering, and model evaluation techniques.
• Work closely with business stakeholders to understand requirements and convert them into data science solutions.
• Develop end-to-end ML pipelines including data preprocessing, model training, testing, and deployment.
• Monitor model performance and retrain models as required.
• Document assumptions, methodologies, and results clearly.
• Collaborate with data engineers and software teams to integrate models into production systems.
• Stay updated with the latest advancements in data science and machine learning.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in computer science, Data Science, Statistics, Mathematics, or related fields.
• 5+ years of hands-on experience in Data Science and Machine Learning.
• Strong proficiency in Python (NumPy, Pandas, Scikit-learn).
• Experience with ML algorithms:
• Regression, Classification, Clustering
• Decision Trees, Random Forest, Gradient Boosting
• SVM, KNN, Naïve Bayes
• Solid understanding of statistics, probability, and linear algebra.
• Experience with data visualization tools (Matplotlib, Seaborn, Power BI, Tableau – preferred).
• Experience working with SQL and relational databases.
• Knowledge of model evaluation metrics and optimization techniques.

Preferred / Good to Have

• Experience with Deep Learning frameworks (TensorFlow, PyTorch, Keras).
• Exposure to NLP, Computer Vision, or Time Series forecasting.
• Experience with big data technologies (Spark, Hadoop).
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Experience with MLOps, CI/CD pipelines, and model deployment.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder interaction skills.
• Ability to work independently and in cross-functional teams.
• Curiosity and willingness to learn new tools and techniques.

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

.