EDA on medical insurance data using Python and R to explore how age, BMI, smoking, and other factors influence claim amounts and health risk profiles.

End-to-end motor insurance analytics project using a two-stage (hurdle) modeling approach to predict claim occurrence and claim severity. Combines business analysis, machine learning, and risk insights to support underwriting, pricing, and claims optimization in General (P&C) Insurance.