Senior Data Scientist

Senior Data Scientist 

Roles & Responsibilities 

• Translate analytical insights into clear, actionable recommendations for product and business stakeholders. 

• Lead endtoend 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 productionready, observable, and scalable. 

• Contribute to AI and GenAI use cases, including intelligent decision systems, AIassisted 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 largescale data and distributed processing (Databricks / Sparklike environments). 

• Experience working with production ML systems. 

• Working understanding of GenAI fundamentals, including Transformers, LLMs, embeddings, and prompting concepts. 

• Strong problemsolving and stakeholder communication skills. 

Good to Have 

• Model monitoring, drift detection, and retraining workflows. 

• Optimization, interpretability (SHAP, feature importance). 

• Exposure to GenAI/LLMbased modeling (usecase dependent). 

• Exposure to Agentic AI concepts (toolusing agents, workflow orchestration). 

• Familiarity with RAGbased 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)