Title: Data Engineer
Location: Pune
Exp: 3-8 Years

KEY RESPONSIBILITIES
- Modelling and analytics: Build, validate, and maintain predictive and statistical models using Python to support product and engineering decisions across a large-scale multi-product workplace.
- Exploratory data analysis: Perform EDA on product and operational datasets identify patterns, anomalies, and opportunities and communicate findings clearly.
- Experimentation: Design and run controlled experiments (A/B tests, hypothesis testing) and report results with appropriate statistical rigour.
- Dashboarding and reporting support: Develop analytics outputs and reporting layers in support of dashboarding work; collaborate with the Data Engineer on data availability and pipeline requirements.
- Feature engineering: Work with raw and transformed data to build features for models; document all transformations and assumptions.
- Ad hoc analytics: Respond to ad hoc data science and analytics requests raised by the Project Lead within agreed hour estimates.
- Model documentation and reproducibility:



Maintain notebooks, model cards, and documentation to a standard that supports knowledge transfer and continuity.
- Collaboration: Partner closely with the Data Engineer (pipelines and data quality) and Cloud Engineer (Azure infrastructure); coordinate with client stakeholders via the Project Lead only.

REQUIRED TECHNICAL SKILL-SET

Skill Area Tools / Platforms Programming Python (strong) pandas, NumPy, scikit-learn, statsmodels Machine Learning Supervised and unsupervised ML regression, classification, clustering, time-series Statistical Analysis Hypothesis testing, A/B testing, statistical inference, EDA Data Visualisation Matplotlib, Seaborn, Plotly; dashboard-ready chart output Big Data / Notebooks Databricks (notebooks and job execution); Jupyter SQL SQL for data extraction, joins, and aggregations Cloud Azure Azure Blob Storage, Azure ML (basic), CosmosDB awareness Version Control Git, GitHub clea

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