Data Science Intern
Developed a churn prediction and win-back model by integrating company-provided data with external sources, such as Realtor and Zillow, to enrich insights on customer behavior and service engagement. Conducted advanced feature engineering, utilizing data on customer demographics, service usage, and housing characteristics to enhance model accuracy. Focused on hyperparameter tuning with an emphasis on metrics that reduce false negatives and accurately capture churned customers. Generated actionable insights on churn drivers, leveraging both internal and external data to support targeted retention strategies.