Sr. Data Scientist / Data Scientist

Williams-Sonoma, Inc.; Maharashtra; On-site; INR 2,400,000 - 3,800,000; Full time

Job summary

Williams-Sonoma, Inc. is seeking a Data Scientist to design ML/analytics solutions across retail and e-commerce use cases. You will translate business inputs into problem statements, perform EDA, build scalable pipelines, and collaborate with engineering to deploy models.

Ideal candidates have 4–8 years of experience, strong Python/SQL, and Spark/PySpark exposure. Retail/e-commerce familiarity is a plus, with focus on customer insights and product search use cases.

Qualifications

• 4–8 years of data science / ML / advanced analytics with production impact.
• Experience with large-scale data; exposure to Spark/PySpark and modern data platforms.
• Strong Python and SQL skills; ability to model and communicate results.
• Excellent communication to influence decisions with data.

Responsibilities

• Design and delivery of ML/analytics solutions across retail and e‑commerce use cases.
• Translate business inputs into ML problem statements, data requirements and KPIs.
• Perform deep EDA, identify drivers and communicate insights to stakeholders.
• Build scalable modeling pipelines and partner with engineering to operationalize models.

Skills

Python (Pandas, NumPy)

SQL

Spark / PySpark

ML / Feature Engineering

Communication / Storytelling

Education

Bachelor’s/Master’s degree in Data Science or related

Tools

MLOps basics

CI/CD basics

Cloud platforms

Job description

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 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.
• 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).