Customer Churn Prediction Using Survival Analysis

Built a survival-analysis system to predict customer churn risk and estimate time-to-churn beyond standard binary classification. Engineered 152 behavioral features from millions of transaction records and developed a calibrated LightGBM, XGBoost, and CatBoost ensemble combined with Lifelines survival models.