Lead I - Data Science - Python, Machine Learning, Spark at Global Digital Transformation Solutions Provider · Pune · 5 - 10 years · ₹21L - ₹30L / yr · Posted 24 Apr 2026

Lead I - Data Science - Python, Machine Learning, Spark
at Global Digital Transformation Solutions Provider
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

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We are looking for a Data Science & Machine Learning Senior Associate with 3–5 years of relevant experience in data science, machine learning, and analytics. The candidate will be responsible for developing predictive models, analyzing complex datasets, building scalable ML solutions, and supporting production-grade data science applications on cloud platforms.
Key Responsibilities
- Develop and implement machine learning and predictive analytics models.
- Perform data analysis, statistical modeling, and optimization to solve business problems.
- Build demand forecasting and predictive models using time-series and other advanced techniques.
- Work with large datasets using Python, SQL, PySpark, and cloud-based data platforms.
- Develop and maintain scalable data pipelines for ML model development and deployment.
- Implement MLOps practices including model deployment, monitoring, retraining, and data-drift detection.
- Collaborate with software engineers, product teams, and business stakeholders to convert business requirements into analytical solutions.
- Validate models for accuracy, robustness, bias, and production readiness.
- Create meaningful visualizations and communicate analytical insights to technical and non-technical stakeholders.
Required Skills
- Python
- SQL
- Data Science & Machine Learning
- Predictive Modeling
- Statistical Analysis
- Machine Learning Algorithms
- Optimization Techniques
- Google Cloud Platform (GCP)
- BigQuery
- Dataflow
- Dataproc
- Data Fusion
- Cloud SQL
- Airflow
- PySpark
- PostgreSQL
- Terraform
- Tekton
- APIs
- MLOps
Preferred Skill
- Java
Good to Have
- Demand Forecasting
- Time-Series Analysis
- Neural Networks
- Ensemble Methods
- Support Vector Machines (SVM)
- Regression and Cluster Analysis
- ML Model Testing
- Bias Detection and Data Drift Monitoring
- Production ML Deployment
- QlikSense
- Automotive or Supply Chain Analytics
Education
Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.Master's degree in a relevant quantitative or technical field is preferred.
🚀 We’re Hiring | Data Scientist 🧠📊
Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!
🔹 Experience: 8+ Years
🔹 Must-Have Skills:
🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization
📍 Location: Pune
💼 Work Mode: Work from Office
If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!
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We are looking for a hands-on Lead Data Scientist with strong analytical, machine learning, and problem-solving skills to work in a client-facing environment.
The role requires someone who can independently identify opportunities, formulate hypotheses, design solutions, and drive initiatives from analysis through experimentation and production implementation. The candidate should also be comfortable guiding team members and working closely with engineering and client stakeholders.
Responsibilities:
- Analyse complex datasets to identify patterns, issues, and opportunities.
- Formulate and validate hypotheses through structured analysis and experimentation.
- Build and improve machine learning and anomaly detection solutions.
- Design end-to-end solutions considering data, modelling, engineering, and production constraints.
- Perform root cause analysis across models, data, and systems.
- Work with engineering teams on feature pipelines, model inference, and production deployment.
- Lead technical discussions with clients and communicate recommendations, trade-offs, and expected impact.
- Guide team members on analysis, modelling, and solution design.
- Proactively identify initiatives and roadmap items that can add value to the project.
Requirements:
- Strong foundation in statistics and machine learning.
- Strong hands-on experience with Python and SQL.
- Hands-on experience with Python ML and data frameworks such as Pandas, NumPy, scikit-learn, TensorFlow/Keras, Dask, Matplotlib, Boto3 SageMaker Python SDK, and Horovod.
- Strong data analysis, hypothesis-generation, and problem-solving skills.
- Experience with standard supervised and unsupervised ML techniques.
- Experience with anomaly detection techniques such as Isolation Forest and Autoencoders.
- Experience building and deploying production ML solutions.
- Working knowledge of data engineering and real-time / batch inference environments.
- Strong communication and stakeholder-management skills.
- Ability to lead technical work and guide cross-functional teams.
Good to Have:
- Experience in fraud detection or risk modelling.
- Experience with Graph Neural Networks.
- Exposure to real-time systems, streaming features, and low-latency data stores.
- Experience in AdTech, e-commerce, gaming, mobile applications, or similar high-volume consumer platforms.
Strong Data Scientist / AI Engineer / Generative AI Engineer profile.
2
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.
3
Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support.
4
Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.
5
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.
6
Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.
7
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.
8
Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.
9
Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.
Mandatory (Education) - B.TECH / M.TECH from Tier 1 Colleges (IIT, NIT, BITS, IIIT, DTU, NSUT) are considered.
Job Description: Python + AI
Company: Wissen Technology
Location: Bangalore, India
Experience: 5+Years
Employment Type: Full-Time
Role: Python + AI / Data Engineer
About the Role
Wissen Technology is looking for experienced Python + AI / Data Engineering professionals to join our technology team in Bangalore. The ideal candidate will have strong hands-on experience in Python, Artificial Intelligence, Generative AI, PySpark, Snowflake, and data pipeline development.
The candidate should be capable of designing and developing scalable data and AI solutions, building robust ETL/ELT pipelines, working with large datasets, and integrating AI/ML capabilities into enterprise applications.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python and PySpark.
- Develop robust ETL/ELT pipelines for processing large volumes of structured and unstructured data.
- Build and optimize data processing solutions using Apache Spark / PySpark.
- Develop data ingestion and transformation pipelines into Snowflake.
- Design and implement scalable Snowflake data models, tables, views, and SQL transformations.
- Work with batch and, where applicable, real-time data processing pipelines.
- Build and integrate AI and Generative AI solutions using Python.
- Develop LLM-based applications, RAG solutions, AI agents, and AI-powered services.
- Integrate AI models with enterprise data platforms and data pipelines.
- Develop REST APIs and microservices using FastAPI, Flask, or Django.
- Perform data cleansing, transformation, validation, and quality checks.
- Optimize PySpark jobs, SQL queries, Snowflake workloads, and data pipelines for performance and scalability.
- Implement data pipeline monitoring, logging, error handling, and alerting.
- Work with cloud platforms such as AWS, Azure, or GCP.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders.
- Participate in technical design, architecture, code reviews, and production support.
- Mentor junior engineers and contribute to engineering best practices.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related field.
- Experience working on enterprise-scale AI and data engineering projects.
- Experience combining Python + PySpark + Snowflake + AI/GenAI in production environments.
- Experience with Databricks is an advantage.
- Experience with AI Agents / Agentic AI and tool/function calling.
- Knowledge of distributed systems and cloud-native architecture.
- Experience leading technical initiatives or mentoring engineering teams.
Location - Bangalore / Pune
Exp - 4 to 10 years
Required
· 3–8 years of relevant experience in data science, AI engineering, or applied machine learning roles.
· Bachelor’s or master’s degree in computer science, Mathematics, Engineering, or a related quantitative field.
· System design: ability to design scalable, reliable, and maintainable systems, including service decomposition, APIs, caching, queues and event-driven architectures, and the trade-offs between latency, throughput, cost, and consistency.
· Strong foundation in data structures and algorithms, with the ability to analyse time and space complexity and choose efficient approaches for large-scale data processing.
· Experience building and operating data-intensive or data-driven applications, such as large-scale data pipelines, batch and streaming processing, or applications whose core features depend on high-volume data.
· Strong hands-on experience in Python.
· Solid foundation in machine learning, NLP, and statistical modeling, including data exploration and visualization.
· Hands-on experience or projects involving LLMs, LangChain, LangGraph, RAG, or agentic AI systems.
· Experience delivering AI/ML solutions into production environments.
· Understanding of text processing and unstructured data.
· Knowledge of software engineering best practices (TDD, refactoring, modular design, version control).
· System design: ability to design scalable, reliable, and maintainable systems, including service decomposition, APIs, caching, queues and event-driven architectures, and the trade-offs between latency, throughput, cost, and consistency.
· Strong foundation in data structures and algorithms, with the ability to analyze time and space complexity and choose efficient approaches for large-scale data processing.
· Experience building and operating data-intensive or data-driven applications, such as large-scale data pipelines, batch and streaming processing, or applications whose core features depend on high-volume data.
· Strong analytical, problem-solving, and communication skills.
· Self-motivated, proactive, and delivery-oriented mindset.
Key Responsibilities
Strong understanding of Machine Learning algorithms (supervised and unsupervised)
Hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, or similar)
Experience in NLP techniques and libraries (NLTK, spaCy, Hugging Face, etc.)
Solid knowledge of Statistics, probability, and data analysis methods
Proficiency in SQL for querying relational databases
Strong programming skills in Python (or similar languages)
Excellent communication skills with the ability to explain complex concepts simply
Required Qualifications
3+ years of hands-on experience as a Data Scientist or in a similar role.
Strong expertise in classical machine learning and regression modeling.
Solid understanding of statistics, including probability, distributions, hypothesis testing,
and correlation analysis.
Proficiency in Python with libraries such as: scikit-learn pandas NumPy
Experience working with structured/tabular data.
Strong problem-solving and analytical thinking skills.
Ability to clearly explain models and results to non-technical stakeholders.
Strong Senior AI Engineer Profile with production-grade LLM and Python expertise
2
Mandatory (Experience 1): Must have at least 3+ years of professional AI/ML engineering experience with demonstrated track record of delivering production-grade AI systems in real-world environments
3
Mandatory (Tech skill 1): Must have strong programming skills in Python and SQL, with hands-on ML/data libraries (scikit-learn, pandas, numpy) and deep-learning frameworks (PyTorch or TensorFlow), plus REST API design
4
Mandatory (Experience 2): Must have hands-on experience building and deploying production-grade ML/LLMs including RAG pipelines, document parsing, information extraction, and text processing on large-scale unstructured data (preprocessing, chunking, embeddings, feature engineering)
5
Mandatory (Tech skill 2): Must have strong NLP / extraction-focused ML depth — transformers, embeddings, vector databases, RAG, LLM integrations, and agentic workflows.
6
Mandatory (Tech skill 3): Must have hands-on experience with AWS (SageMaker, Bedrock, EC2, Lambda) and Azure (AI Foundry, Azure OpenAI) for model training, fine-tuning, deployment, and inference at scale
7
Mandatory (Tech skill 4): Must have experience with multi-agentic frameworks / orchestration tools (Claude Code, LangGraph, LangChain, CrewAI)
8
Mandatory (Tech skill 5): Must have hands-on experience with MLOps ecosystem including experiment tracking (MLflow, Weights & Biases), model versioning/registry, automated retraining, and CI/CD (GitHub Actions, Azure DevOps, Docker, Kubernetes)
9
Mandatory (Tech skill 6): Must have experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement, plus AI observability (Prometheus, Grafana, SLOs).
10
Mandatory (Team Leadership): Must have experience leading projects or teams, managing technical deliverables, and mentoring, with strong problem-solving in ambiguous challenges
11
Mandatory (Education) - B.Tech or B.E. If graduated in BCA or BCS, they should have a Maters or Post graduation
12
Mandatory (Company): B2B Tech/Consulting/B2B Software

Job Summary
We are looking for an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and AI solutions that address complex business problems. The ideal candidate should have strong hands-on experience in Python, Machine Learning, Generative AI, LLMs, and AI/ML deployment, with the ability to work across the complete AI/ML lifecycle.
Key Responsibilities
- Design, develop, and deploy scalable Machine Learning and AI models for real-world business use cases.
- Build and optimize ML pipelines covering data preparation, feature engineering, model development, evaluation, and deployment.
- Develop solutions using Generative AI, Large Language Models (LLMs), NLP, and deep learning.
- Work with LLMs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
- Integrate AI/ML models with enterprise applications and APIs.
- Fine-tune and evaluate ML/LLM models based on business requirements.
- Implement MLOps practices for model versioning, deployment, monitoring, and continuous improvement.
- Collaborate with Data Scientists, Software Engineers, Architects, Product Managers, and business stakeholders.
- Conduct model performance evaluation, optimization, and troubleshooting.
- Ensure AI solutions meet requirements around security, scalability, reliability, responsible AI, and data privacy.
- Stay current with emerging AI/ML technologies, frameworks, and industry best practices.
Required Skills
- Strong programming experience in Python.
- Strong understanding of Machine Learning algorithms, statistics, and data structures.
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
- Experience with Generative AI and LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, or open-source models.
- Strong knowledge of Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
- Experience with NLP, deep learning, or computer vision is an advantage.
- Experience developing and consuming REST APIs and microservices.
- Working knowledge of SQL and NoSQL databases.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Understanding of Docker, Kubernetes, CI/CD, and MLOps.
- Familiarity with Git and modern software development practices.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- 4 years of relevant experience in AI/ML engineering or a related field.
- Experience building and deploying production-grade AI/ML solutions.
- Enterprise application development experience.
- Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or similar managed AI platforms.
- Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable AI frameworks is a plus.
- Experience with AI/ML model monitoring, evaluation, and optimization.
What You Bring
- Strong problem-solving and analytical skills.
- Ability to translate business requirements into practical AI/ML solutions.
- Strong software engineering and debugging capabilities.
- Ability to work independently as well as collaboratively in a cross-functional environment.
- Good communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.
Keywords
AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI
Location: Gurugram
Work mode: Hybrid
Strong Senior AI Engineer Profile with production-grade LLM and Python expertise
2
Mandatory (Experience 1): Must have at least 3+ years of professional AI/ML engineering experience with demonstrated track record of delivering production-grade AI systems in real-world environments
3
Mandatory (Tech skill 1): Must have strong programming skills in Python and SQL, with hands-on ML/data libraries (scikit-learn, pandas, numpy) and deep-learning frameworks (PyTorch or TensorFlow), plus REST API design
4
Mandatory (Experience 2): Must have hands-on experience building and deploying production-grade ML/LLMs including RAG pipelines, document parsing, information extraction, and text processing on large-scale unstructured data (preprocessing, chunking, embeddings, feature engineering)
5
Mandatory (Tech skill 2): Must have strong NLP / extraction-focused ML depth — transformers, embeddings, vector databases, RAG, LLM integrations, and agentic workflows.
6
Mandatory (Tech skill 3): Must have hands-on experience with AWS (SageMaker, Bedrock, EC2, Lambda) and Azure (AI Foundry, Azure OpenAI) for model training, fine-tuning, deployment, and inference at scale
7
Mandatory (Tech skill 4): Must have experience with multi-agentic frameworks / orchestration tools (Claude Code, LangGraph, LangChain, CrewAI)
8
Mandatory (Tech skill 5): Must have hands-on experience with MLOps ecosystem including experiment tracking (MLflow, Weights & Biases), model versioning/registry, automated retraining, and CI/CD (GitHub Actions, Azure DevOps, Docker, Kubernetes)
9
Mandatory (Tech skill 6): Must have experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement, plus AI observability (Prometheus, Grafana, SLOs).
10
Mandatory (Team Leadership): Must have experience leading projects or teams, managing technical deliverables, and mentoring, with strong problem-solving in ambiguous challenges
11
Mandatory (Education) - B.Tech or B.E. If graduated in BCA or BCS, they should have a Maters or Post graduation
12
Mandatory (Company): B2B Tech/Consulting/B2B Software










