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CASE STUDIES

Customer Churn & Revenue Prediction — Python & Tableau
Built a logistic regression model (AUC 0.81) to predict customer churn for a telecom provider, identifying $1.4M in recoverable revenue. Analyzed behavioral and demographic data to segment high-risk customers and delivered an interactive Tableau dashboard to support retention strategy.
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