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Data Scientist

Job in 411001, Pune, Maharashtra, India
Listing for: Williams-Sonoma, Inc.
Full Time position
Listed on 2026-02-24
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist
Job Description & How to Apply Below
Job Role - Sr. / Data Scientist

Job Location - Pune (Hybrid)

Job Description:

Sr. / Data Scientist

About the Role
Williams-Sonoma is hiring a Sr. / Data Scientist to drive measurable business impact across our retail and digital ecosystem. This role is for a strong individual contributor who can lead end-to-end implementation from problem framing and experimentation to production deployment, working closely with product, merchandising, marketing, supply chain, and engineering teams.

Key Responsibilities
Lead the design and delivery of ML/analytics solutions (forecasting, propensity, segmentation, churn, ranking, personalization) across retail and e-commerce use cases.
Translate business inputs into clear 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.
5+ years in data science / applied ML / advanced analytics with demonstrated production impact.
Strong Python (Pandas, Num Py, 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).
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