Partner with senior stakeholders to understand problems, frame them as data science questions, and translate requirements into well-scoped, actionable solutions
Conduct extensive exploratory data analysis (EDA) to uncover patterns, validate assumptions, and identify the right modeling approach
Build, validate, and maintain machine learning models end-to-end from problem framing to deployment and monitoring
Continuously optimize existing models for accuracy, robustness, and business impact
Write clean, efficient, production-ready code in Python and SQL
Work with large-scale data using AWS SageMaker, Redshift/Snowflake, and S3
Apply critical thinking to challenge assumptions, validate results, and ensure models solve the actual business problem, not just a technically interesting one
Present findings and recommendations clearly to both technical and non-technical stakeholders