AYB Data Science Competition (First Place)

Completed 75+ hours of intensive training to build a predictive churn model for a bank customer dataset with

85% accuracy on a dataset of 10,000+ records.

• Achieved a 0.98 AUC score using a fine-tuned Random Forest Classifier with precision and recall above 0.85.

Proposed strategies projected to reduce churn by 15%.