• Developed deep learning models for customer lifetime value (CLV) prediction, boosting targeted retention campaigns efficiency by 30%. • Designed and deployed real-time fraud detection pipeline using PySpark and Scikit-learn, preventing $400K+ in daily losses. • Led statistical validation of new recommendation algorithms through rigorous multivariate testing.

• Created ETL pipelines in Python/SQL, streamlining data warehouse updates and saving 10 engineering hours weekly. • Built interactive dashboards in Tableau for executive reporting, visualizing user acquisition and churn patterns.