Key Responsibilities Design and delivery of ML/analytics solutions (forecasting, propensity, segmentation, churn, ranking, personalization) across retail and e-commerce use cases.

Translate business inputs into transparent ML problem statements, data requirements, KPIs, and success metrics.

Perform deep EDA, identify drivers/opportunities, and communicate insights through strong storytelling tailored to business stakeholders.

Build robust feature engineering and scalable modeling pipelines (Spark/PySpark preferred).

Select appropriate model evaluation methods (metrics, validation strategy, leakage prevention, error analysis) and ensure reliability.

Partner with engineering/platform teams to operationalize models (batch/real-time), including monitoring, drift checks, and retraining strategy.

Drive technical documentation, code quality, and best practices; contribute to team standards and reviews.

Hands-on exposure to Computer Vision and Generative AI/LLMs (e.g., RAG, embeddings, prompt engineering, agent workflows)



for retail use cases such as product search, customer support, and content understanding.

Required Qualifications Bachelor’s/Master’s (or equivalent experience) in Data Science, CS, Statistics, Math, or related field.

4-8 years in data science / applied ML / advanced analytics with demonstrated production impact.

Strong Python (Pandas, NumPy, Scikit-learn) and solid SQL.

Strong foundations in classical ML, feature engineering, and model evaluation.

Experience working with large-scale data; exposure to Spark/PySpark and modern data platforms.

Strong communication and ability to influence decisions with data.

Preferred Qualifications Retail/e-commerce experience (demand forecasting, pricing/promo, inventory, conversion, customer lifecycle).

Exposure to MLOps (CI/CD basics, monitoring, experiment tracking, drift/retraining). Cloud experience (Azure preferred).

📌 Sr. Data Scientist / Data Scientist (Pune)
🏢 Williams Sonoma
📍 Pune