Case study
Customer Churn Prediction System
ML pipeline with KPI dashboards to recover churn risk and revenue leakage.
scikit-learnTableauPythonFeature Engineering
Problem
Customer attrition signals were hard to track across disparate systems.
Approach
Built predictive models with feature engineering and automated dashboards for actionable insights.
Security considerations
Applied least-privilege analytics access and data validation for modeling inputs.
Results
Analyzed 50K+ customers and recovered $40K in leakage with Tableau KPIs.
50K+ customers$40K recovered
Tech stack
scikit-learnTableauPythonFeature Engineering
What I'd improve next
Add drift monitoring and automated model retraining.