Developed a real-time fraud detection system using machine learning

Trained an XGBoost model on the IEEE-CIS Fraud Detection dataset (590,540 rows, 393 features), achieving 97% accuracy and 0.91 ROC AUC score

Designed a real-time ETL pipeline, processing live transactions via Google Cloud Firestore & Functions.