Summary
Led advanced data science initiatives to enhance business performance, customer engagement, and operational efficiency through predictive modeling and AI solutions.
Highlights
Pioneered the development and deployment of a customer churn prediction model, achieving a 50% reduction in churn and significantly enhancing customer retention strategies.
Engineered a customer segmentation model, elevating targeted marketing effectiveness and contributing to a 30% increase in sales.
Designed and implemented a robust fraud detection system, boosting identification accuracy by 40%.
Automated critical business intelligence dashboards, enhancing data accessibility and reducing reporting time.
Spearheaded and executed A/B testing initiatives, optimizing customer engagement strategies and campaign performance.
Integrated diverse external data sources (NIBSS, Credit Bureau, Google Maps) to enrich datasets and enhance predictive modeling accuracy.
Developed and deployed an internal GPT-based AI chatbot, empowering employees with instant access to customer insights and business intelligence reports.
Optimized machine learning operations by leveraging MLflow and Azure AutoML, streamlining model building, tracking, and deployment processes across multiple machine learning models.