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 (Pune)
🏢 Williams Sonoma
📍 Pune