Senior Data Scientist

Senior Data Scientist

Experience required: 5 - 8 yrs

Roles & Responsibilities

• Translate analytical insights into clear, actionable recommendations for product and business stakeholders.
• Lead end‑to‑end data science and ML initiatives, from problem framing and feature engineering to deployment and performance evaluation.
• Develop and optimize machine learning models (classification, regression, boosting, ranking, forecasting) that drive measurable business impact.
• Partner with ML Engineering, Platform, and MLOps teams to ensure solutions are production‑ready, observable, and scalable.
• Contribute to AI and GenAI use cases, including intelligent decision systems, AI‑assisted workflows and Agentic AI systems.
• Mentor junior data scientists and promote high standards of modeling rigor and code quality.

Skills

Must Have

• Strong machine learning fundamentals, statistics and model evaluation.
• Advanced Python and SQL for data science and modeling.
• Experience with large‑scale data and distributed processing (Databricks / Spark‑like environments).
• Experience working with production ML systems.
• Working understanding of GenAI fundamentals, including Transformers, LLMs, embeddings, and prompting concepts.
• Strong problem‑solving and stakeholder communication skills.

Good to Have

• Model monitoring, drift detection, and retraining workflows.
• Optimization, interpretability (SHAP, feature importance).
• Exposure to GenAI/LLM‑based modeling (use‑case dependent).
• Exposure to Agentic AI concepts (tool‑using agents, workflow orchestration).
• Familiarity with RAG‑based systems and retrieval strategies.

Tech Stack / Tools

Must Have

• Python, SQL
• ML algorithms (Bagging, Boosting, Neural Nets)
• Databricks & Spark
• Git / version control
• ML experimentation and evaluation tools
• Data visualization and reporting tools
• Cloud computing - AWS and/or Azure

Good to Have

• Cloud platforms (Azure / AWS / GCP)
• ML experimentation and monitoring tools
• GenAI tooling (LLM frameworks, embeddings, vector stores)