Data Scientist

About the Company: 

WebMD Health Corp., an Internet Brands Company, is the leading provider of health information services, serving patients, physicians, health care professionals, employers, and health plans through our public and private online portals, mobile platforms, and health-focused publications. The WebMD Health Network includes WebMD Health, Medscape, Jobson Healthcare Information, prIME Oncology, MediQuality, Frontline, QxMD, Vitals Consumer Services, MedicineNet, eMedicineHealth, RxList, OnHealth, Medscape Education, and other owned WebMD sites. WebMD®, Medscape®, CME Circle®, Medpulse®, eMedicine®, MedicineNet®, theheart.org®, and RxList® are among the trademarks of WebMD Health Corp. or its subsidiaries. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

For Company details, visit our website: www.webmd.com

Experience: 3+ years

Qualification: Master's degree in Computer Science, Statistics, Mathematics, or a related field.

Work Timings: 2 PM to 11 PM IST

Position Requirement:

• Write clean and efficient code in Python and/or R for data analysis, statistical modeling, and machine learning tasks.
• Apply statistical and machine learning techniques to analyze large datasets and extract meaningful patterns, trends, and insights. Develop and implement predictive models for various business applications.
• Formulate hypothesis tests and design experiments to validate assumptions, measure the impact of changes, and optimize decision-making processes.
• Demonstrate strong SQL skills for efficient data querying and manipulation using window functions.
• Work with large datasets and ensure data quality and accuracy.
• Experience with dashboarding tools like Tableau is a plus to visualize and present data-driven insights to both technical and non-technical stakeholders.
• Ability to communicate complex technical concepts and insights in a clear and concise manner to both technical and non-technical audiences. Engage with the leadership team and clients to understand business requirements and provide data-driven solutions.
• Work with real world case studies in Data Science and a chance to implement various modelling techniques. Opportunity to independently execute and lead analytical projects and assignments.
• Help solve some challenging Healthcare related digital marketing problems globally. Transform business question into data requirements; collect and merge the data; analyse the data, link it to the business reality and present the results
• Develop predictive models and machine learning algorithms to study change in physician prescribing behaviour as well as WebMD integrated campaign response behaviour. Build analysis to understand user engagement and behaviours across various WebMD products.

Technical Skills needed:

1.Experience with data manipulation in SQL environment is a must. Experience with BigQuery/Vertica data warehousing is good to have

• Experience with statistical and data manipulation tools such as Python or R is a must 
• Need very good expertise in using Microsoft Excel, and Microsoft PowerPoint. Excellent presentation skills required
• Experience developing statistical models like hypothesis testing, regression models, classifications models, forecasting etc is a must 
• Algorithm designing and implementation skills in R or Python is required 

Requirements

• B.Tech/B.E. / MSc Statistics from premier institutes with
• Minimum 80% marks in 10th and 12th
• Minimum 75% marks in graduation
• 2-5 years of relevant work experience in analytics field
• Proven experience in data science, statistical modeling, and machine learning applications.
• Strong proficiency in Python and/or R programming languages.
• Solid understanding of statistical concepts, hypothesis testing, and experimental design
• Expertise in SQL for data querying and manipulation.
• Familiarity with dashboarding tools is a plus.
• Excellent presentation, communication and interpersonal skills.

Job Summary:

We are looking for a skilled Data Scientist with strong expertise in demand forecasting, predictive analytics, and emerging Generative AI technologies. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and LLM-based solutions, along with proficiency in Python, SQL, Power BI, and advanced Excel. This role involves building scalable forecasting models and leveraging AI/GenAI to deliver actionable business insights.

Key Responsibilities:

• Develop and deploy demand forecasting models using machine learning and deep learning techniques.
• Analyze historical data to identify trends, seasonality, and demand patterns.
• Build predictive models to improve supply chain and inventory planning.
• Work with large datasets using Python and SQL for data extraction, transformation, and analysis.
• Design dashboards and reports using Power BI for business stakeholders.
• Utilize advanced Excel techniques (Pivot Tables, Power Query, formulas) for analysis and reporting.
• Build and integrate NLP-based solutions for text data analysis and insights.
• Develop and implement LLM-based applications using Generative AI frameworks.
• Design and deploy RAG (Retrieval-Augmented Generation) pipelines for intelligent data retrieval and response generation.
• Collaborate with cross-functional teams (operations, finance, product) to align forecasting and AI solutions.
• Continuously improve model accuracy and performance through experimentation and optimization.

Required Skills:

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
• Solid understanding of machine learning & deep learning algorithms.
• Experience in demand forecasting / time-series analysis (ARIMA, Prophet, LSTM, etc.).
• Hands-on experience with NLP techniques and libraries (NLTK, SpaCy, Transformers).
• Experience working with LLMs and Generative AI frameworks (OpenAI, Hugging Face, LangChain, etc.).
• Strong understanding of RAG architectures and vector databases (FAISS, Pinecone, etc.).
• Advanced knowledge of SQL for data manipulation.
• Hands-on experience with Power BI for visualization and reporting.
• Expertise in advanced Excel (Power Query, dashboards, data modeling).
• Strong analytical and problem-solving skills. 

Preferred Qualifications:

• Experience in supply chain, logistics, or e-commerce forecasting.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Familiarity with data pipelines and ETL processes.
• Understanding of business metrics and KPIs related to demand planning.

Role overview

Antier Solutions is hiring a Business & Solutions Consultant to lead discovery, solution design and delivery alignment for a large enterprise client.

The role is domain agnostic: we want a structured problem-solver who can step into any industry, learn it fast and turn business goals into technology solutions our engineering teams can build.

Item Detail

1. Position                                       Business & Solutions Consultant
2. Engagement                               Enterprise client account (client-facing)
3. Reports to                                    Delivery Head / Practice Lead
4. Experience                                  6–12 years in consulting or digital transformation
5. Preferred background                Big 4 or equivalent top-tier consulting firm
6. Location                                       Mohali / Chandigarh (hybrid; client travel as needed)

Key responsibilities

Client engagement and discovery

• Act as the trusted advisor to client senior stakeholders (CXO, VP, Director level).

• Run discovery workshops, stakeholder interviews and process walkthroughs to capture business goals, pain points and constraints.

• Quickly build working knowledge of the client's industry, operating model, regulations and competitors.

Business analysis and solution design

• Convert business needs into business requirement documents, functional specifications, user stories and acceptance criteria.

• Map as-is and to-be processes, run gap and fit-gap analysis, and define the target operating model where needed.

• Work with architects and engineering leads to shape technically feasible solutions across web, mobile, cloud, data and AI platforms.

• Build business cases, ROI and cost-benefit models, and solution roadmaps with clear phasing.

Delivery and governance

• Own scope, requirements traceability and change control; keep business and technology teams aligned through the delivery cycle.

• Support sprint planning, backlog prioritisation, UAT and go-live readiness.

• Track risks, dependencies and assumptions; escalate early with a recommended mitigation.

• Prepare steering committee decks, status reports and executive summaries.

Pre-sales and growth

• Support proposals, RFP/RFI responses, solution presentations and estimates with the Business Development team.

• Identify upsell and expansion opportunities within the client account.

• Join client and prospect meetings with the sales team as the business and solution expert, and lead technical-business discovery calls to qualify opportunities.

• Translate client needs into compelling solution narratives, demos, proof-of-concept scopes and value propositions that differentiate Antier.

• Prepare effort estimates, commercial models, pricing inputs and delivery plans with delivery and finance teams.

• Co-own large proposals and enterprise deal pursuits: win themes, executive presentations and defense of the solution during client negotiations.

• Build reusable sales assets such as case studies, capability decks, solution accelerators and industry point-of-view papers.

• Use consulting networks and industry knowledge to open doors, support lead generation and strengthen relationships with enterprise decision makers.

• Provide market and competitor insights to the leadership team to sharpen go-to-market strategy and positioning.

• Support a smooth handover from sale to delivery so that commitments made in pre-sales are executed.

Required qualifications and experience

• Bachelor's degree in engineering, business or a related field; MBA or equivalent postgraduate degree from a reputed institute preferred.

• 6–12 years of experience in management or technology consulting, with at least 3 years at a Big 4 firm (Deloitte, EY, KPMG, PwC) or a comparable firm such as Accenture, McKinsey, BCG or Bain.

• Proven record on client-facing engagements for large enterprises across more than one industry or domain.

• Hands-on experience in requirements gathering, process mapping and solution definition for technology or digital transformation programs.

• Experience working with engineering teams on delivery, in Agile or hybrid models.

• Prior exposure to enterprise platforms, data and analytics, cloud, AI or blockchain programs is a strong plus.

• Demonstrated experience supporting pre-sales or business development: proposals, RFP responses, solution pitches and client presentations that contributed to deal wins.

Skills and competencies

       Area                                                                                                                        What we look for

Structured problem solving                                            Hypothesis-driven thinking, issue trees, MECE analysis, root-cause analysis

Domain agility                                                                  Learns a new industry within weeks and speaks credibly with business owners

Communication                                                               Crisp writing, executive presentations, workshop facilitation, active listening

Stakeholder management                                              Handles senior and conflicting stakeholders; builds trust and drives decisions

Technical fluency                         Understands architecture, APIs, integrations, data flows and cloud basics well enough to challenge and translate  

Analytical tools                            Advanced Excel and PowerPoint; Jira, Confluence, Visio or Lucidchart; working knowledge of Power BI or Tableau

Delivery discipline                                                           Agile and Scrum, backlog management, risk and change management

Ownership                                                                       Works independently on ambiguous problems and takes accountability for outcomes

Good to have, and what we offer

Good to have

• Certifications such as CBAP, PMP, PMI-PBA, CSPO or TOGAF.

• Experience with global clients across the US, UK, Middle East or APAC.

• Exposure to RFP and proposal writing for technology services.

What we offer

• Direct exposure to a large enterprise client and senior decision makers.

• Close collaboration with Antier's architects and engineering teams on AI, blockchain, fintech and enterprise platforms.

• A defined growth path into Principal Consultant or Client Partner roles.

• Competitive compensation aligned to Big 4 experience, with performance-linked rewards.

Designation: AI Adoption specialist/AI Consultant

Location: Ahmedabad

Work Timings: Primarily Normal Shift (Flexible to support US clients)

Role Overview:

We are seeking a highly skilled and client-centric AI Consultant/AI Adoption Specialist to join our growing team. In this pivotal role, you'll serve as a vital link between our clients' strategic objectives and the transformative power of AI. You'll primarily focus on understanding their needs, scoping opportunities, and architecting actionable AI roadmaps.

Key Responsibilities:

 Collaborate closely with clients to understand their challenges and identify opportunities to apply AI.

 Assess client requirements and prepare solution strategies using AI tools and methodologies.

 Work with internal teams to design, propose, and help execute AI-powered solutions.

 Provide AI-based recommendations that align with the client’s business objectives.

 Communicate technical possibilities in a business-friendly manner to decision-makers.

 Take ownership of the client journey from discovery to implementation and support.

 Stay updated with AI trends, tools, and real-world use cases that can benefit clients.

Required Skills & Qualifications:  Minimum 2+ Years of hands on experience into Custom AI Development.  Minimum 3+ years of experience in roles like Project Manager, Customer Success Manager, or Account Manager, preferably in a service-based company or digital agency.  Strong understanding of AI concepts, trends, and tools (e.g., NLP, ML, Chatbots, Automation, native cloud technologis).  Some hands-on experience in AI projects – either through execution, coordination, or implementation.  Ability to manage multiple client engagements and communicate effectively with both technical and non-technical stakeholders.  Strong problem-solving mind set with the ability to translate business needs into AI opportunities.  Flexible to work with international clients, especially in the US time zone as needed.

Role Overview 

As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact. 

Key Responsibilities 

Data Science & Machine Learning 

• Analyze structured and unstructured data to identify patterns, trends, and business opportunities.  
• Perform exploratory data analysis (EDA), feature engineering, and data preparation.  
• Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.  
• Apply statistical techniques to solve business problems and validate model performance.  
• Design and execute experiments to improve model accuracy and business outcomes.  

 AI Solution Development 

• Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.  
• Translate business requirements into scalable data science approaches.  
• Contribute to Generative AI and advanced analytics initiatives where applicable.  
• Document methodologies, model performance, and key findings.  

 Required Technical Skills 

• Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.  
• Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.  
• Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.  
• Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.  
• Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.  
• Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.  
• Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.  
• Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.  
• Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred. 

Preferred Qualifications 

• Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.  
• 2–4 years of experience developing machine learning or data science solutions.  
• Experience working on end-to-end data science projects in a business environment.  

 Nice to Have 

• Exposure to Generative AI, LLMs, RAG, or Agentic AI.  
• Experience with Computer Vision or Natural Language Processing (NLP).  
• Familiarity with cloud-based AI platforms.  
• Knowledge of construction, engineering, manufacturing, or industrial domains.  
• Participation in hackathons, research, Kaggle competitions, or open-source projects.  

 Soft Skills 

Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.

Data Scientist – Machine Learning & Applied Analytics. 

Location: Bengaluru 

Experience: 5–8 Years 

Role Type: Full-Time 

Business Unit: Products & Platforms (PMG) 

Role Overview 

We are looking for a Data Scientist – Product Analytics & Machine Learning to help build differentiated analytics and ML capabilities across our product and platform portfolio, including MOBIUS+ and Signate. 

This is a hands-on product-focused role responsible for translating real-world customer and domain problems into scalable analytics and machine learning solutions. The role will work across the complete lifecycle — from data exploration and experimentation through model development, validation, productization and production monitoring. 

The Data Scientist will also work closely with Tata Elxsi's internal analytics teams, specialist solution providers and academic/research institutions to evaluate, integrate and evolve analytical capabilities as part of our products. 

Key Responsibilities 

Product Analytics & ML 

• Translate product and customer problems into well-defined analytics and ML use cases. 
• Perform data exploration, feature engineering, statistical analysis and experimentation. 
• Develop, train, validate and optimize machine learning and predictive models. 
• Define appropriate model performance metrics, benchmarks and acceptance criteria. 
• Convert prototypes and experiments into scalable, production-ready capabilities. 
• Work with Product, Architecture and Engineering teams to integrate models and analytics into SaaS products and platforms. 

Model Evaluation & Productization 

• Evaluate models and analytical solutions developed by internal teams, technology partners and specialist solution providers. 
• Assess model assumptions, data requirements, accuracy, robustness, explainability and limitations. 
• Benchmark alternative models/approaches and provide evidence-based recommendations. 
• Establish practices for model versioning, validation, monitoring, drift detection and continuous improvement. 
• Ensure that externally sourced models can be effectively integrated, governed and evolved within the product. 

Collaboration & Research 

• Collaborate with Tata Elxsi's broader AI, analytics and domain teams and leverage specialist capabilities where required. 
• Work technically with external solution providers to understand and integrate their algorithms and models. 
• Engage with researchers and academic institutions such as IITs, NITs and IISc on advanced analytics and ML opportunities. 
• Evaluate research, algorithms and PoCs and help translate promising approaches into production-grade product capabilities. 
• Build reusable analytical assets, datasets, features, evaluation frameworks and know-how across the product portfolio. 

Technical Skills 

• Strong foundation in statistics, probability, machine learning and data analysis. 
• Strong hands-on programming skills in Python and common data science libraries. 
• Experience with Pandas, NumPy, scikit-learn and relevant ML frameworks. 
• Experience developing predictive models using structured and time-series data. 
• Understanding of supervised/unsupervised learning, anomaly detection, forecasting, classification and regression techniques. 
• Experience with feature engineering, model selection, hyperparameter optimization and model evaluation. 
• Good understanding of model explainability, bias, uncertainty and robustness. 
• Working knowledge of SQL and large-scale data processing. 
• Experience deploying or integrating ML models into production applications through APIs, services or ML pipelines. 
• Understanding of MLOps, including model versioning, experiment tracking, monitoring and model lifecycle management. 
• Experience with cloud environments, preferably AWS, is desirable. 
• Exposure to GenAI/LLMs and their application within product analytics is an advantage. 

Product & Engineering Mindset 

• Ability to move beyond experimentation and think about how analytics becomes a repeatable product capability. 
• Strong problem-solving ability and comfort working with incomplete or imperfect real-world datasets. 
• Ability to distinguish between an interesting analytical result and one that creates measurable customer/product value. 
• Comfortable working closely with Product Managers, Domain SMEs, Architects and Software Engineers. 
• Ability to critically evaluate third-party algorithms and models rather than treating external solutions as black boxes. 
• Strong technical communication skills and ability to explain analytical concepts and model outcomes to both technical and business stakeholders. 

Preferred Experience 

• 5–8 years of relevant experience in Data Science, Machine Learning, Applied Analytics or related roles. 
• Experience building ML/analytics capabilities that have been deployed into production products or platforms. 
• Experience working with automotive, mobility, connected vehicle, battery/EV, IoT or industrial datasets is desirable but not mandatory. 
• Experience collaborating with technology partners, research organizations or academic institutions is an advantage. 
• Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related quantitative discipline preferred. 

What Success Looks Like 

The successful candidate will help PMG establish a strong internal Data Science & ML capability that can build differentiated analytics, intelligently leverage Tata Elxsi's broader capabilities and external specialists, and retain the knowledge and ownership required to continuously evolve analytics as a core part of our products and platforms. 

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.

Job Title: Senior Data Analyst

Location: Sharnam Metrolinks, Amraiwadi, Ahmedabad

Working Days: 6 Days a Week

Department: MDO

Reporting To: COO

Employment Type: Full-Time

Job Summary

We are seeking a highly analytical and detail-oriented Senior Data Analyst to lead data management, reporting, automation, and system development initiatives across the organization.

The role focuses on transforming raw data into meaningful insights, designing and implementing automated systems, strengthening data structures, and supporting cross-functional teams with accurate, actionable intelligence to drive strategic and operational business decisions.

Key Responsibilities

1. Data Management & Reporting

● Collect, clean, validate, and consolidate data from multiple internal and external sources.

● Prepare and deliver daily, weekly, and monthly MIS reports for management and departments.

● Design, develop, and maintain dashboards to track KPIs, performance metrics, and operational trends.

2. Database & Data Accuracy Management

● Manage and regularly update internal databases, spreadsheets, and reporting systems.

● Ensure data accuracy, consistency, integrity, and confidentiality across all platforms.

● Implement best practices for data validation, version control, and audit checks.

3. Data Analysis & Business Insights

● Analyze large and complex datasets to identify trends, patterns, gaps, and anomalies.

● Translate data findings into clear, actionable insights and recommendations to support

strategic and operational decision-making.

4. Reporting Automation, System Recommendation & Implementation

● Identify opportunities to replace manual or semi-manual processes with automated, data-driven systems.

● Design and implement automated reporting frameworks, dashboards, and data pipelines using Excel (Power Query, VBA, Macros), SQL, BI tools, and Python.

● Proactively suggest new automation tools, system enhancements, or integrations to

improve efficiency, accuracy, and scalability.

● Lead the end-to-end implementation of approved automation initiatives, including requirement gathering, system design, testing, deployment, and stabilization.

● Continuously monitor and optimize automated systems in line with business growth and evolving data needs.

5. Cross-Functional Coordination & Support

● Collaborate with Sales, HR, Finance, Operations, and other departments to understand

reporting and data requirements.

● Provide support for ad-hoc analysis, custom reports, and special data requests.

● Act as a data partner to department heads for decision support and performance tracking.

6. Documentation & Compliance

● Maintain complete and updated documentation for MIS processes, reports, data models,

automation logic, and system changes.

● Ensure compliance with company data governance policies and applicable data protection standards.

System Development & Data Structuring Responsibilities

● Study and understand departmental workflows to evaluate how data is generated, processed, and utilized.

● Review existing manual and digital data systems to identify operational gaps, risks, and

mprovement opportunities.

● Recommend structured data models, reporting formats, and storage solutions aligned with

business requirements.

● Coordinate with department heads to define data structures, access levels, and reporting

standards.

● Implement new or upgraded data systems (Excel-based models, cloud platforms, ERP

integrations) with minimal operational disruption.

● Design structured data formats and role-based access controls to ensure secure and

organized data management.

● Train employees on newly implemented systems and provide post-implementation

support.

● Monitor system performance, resolve issues, and continuously improve systems based on

user feedback and organizational growth.

Qualifications & Experience

● Bachelor’s degree in Commerce, Statistics, Computer Applications, or a related field.

● 3–5 years of experience in data analytics, reporting, or system automation roles.

● Strong analytical thinking, logical reasoning, and problem-solving abilities.

● High attention to detail with excellent organizational and documentation skills.

Technical Skills (Must Have)

● Advanced Excel: Power Query, Power Pivot, VBA basics, Macros, Charts

● BI Tools: Power BI or Tableau (DAX, data modeling, dashboard optimization)

● Google Apps Script: Automation in Google Sheets, custom functions, triggers, API integrations, workflow optimization

● Vlook

Preferred Skills

● Strong verbal and written communication skills

● Ability to handle sensitive and confidential information responsibly

● Quick learner with a tech-savvy, improvement-driven, and solution-oriented mindset

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. 

Strong Data Analyst Profile with Python, SQL, and data-pipeline expertise, ideally with retail / e-commerce datasets

2

Mandatory (Experience 1): Must have 4+ years of hands-on data-analyst experience, working with large datasets across areas such as sales, inventory, pricing, promotions, and customer behaviour.

3

Mandatory (Tech skill 1): Must have strong hands-on Python for data processing, transformation, automation, and analysis

4

Mandatory (Tech skill 2): Must have strong SQL skills, including complex queries, joins, aggregations, and data validation.

5

Mandatory (Tech skill 3): Must have a solid understanding of Data Lake architecture, ingestion, storage, and processing workflows

6

Mandatory (Tech skill 4): Must have hands-on experience with ETL / ELT pipelines, data integration, and transformation

7

Mandatory (Tech skill 5): Must have experience with Azure or GCP data services.

8

Mandatory (Tech skill 6): Must have understanding of or experience with Databricks and distributed data processing.

9

Mandatory (Tech skill 7): Must have knowledge of data modeling, data warehousing, and Lakehouse architecture

10

Mandatory (Tech skill 8): Must have experience with Power BI, Tableau, or Excel for reporting.

11

Mandatory (Communication): Must have strong analytical, documentation, and stakeholder-communication skills.

12

Mandatory (Education): Must hold a Bachelor’s degree in Computer Science, IT, Engineering, or a related field.

13

Mandatory (Note1): This is a 6-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)