SaaS Churn Prediction Model with Advanced Feature Engineering

Develop a comprehensive Python machine learning pipeline to predict customer churn for a SaaS platform using pandas, scikit-learn, and advanced feature engineering techniques. The model should incorporate customer interaction logs, usage metrics, billing history, and support ticket data. Implement cross-validation with stratified K-fold, create an interpretable model using SHAP values, and generate a deployment-ready script that can be integrated into existing customer success workflows. Include detailed documentation explaining feature importance, model performance metrics, and potential business interventions based on churn predictions.