Risk Analyst Intern
Current• Analyzed fraud survey data for over 10,000 accounts using SAS & SQL, evaluating Net Promoter Score.• Conducted in-depth analysis of multiple account holder (MAP) customers' attributes and utilization patterns, processing data for over 850,000 accounts using SAS and advanced statistical analysis techniques.• Developed and implemented machine learning models for propensity score matching, employing logistic regression, SMOTE, and AUC-ROC, resulting in a 60% improvement in match accuracy.• Automated reporting processes and optimized data workflows using SAS, SQL, and Python, reducing manual effort by 40% and significantly improving data retrieval efficiency.
Jun 2024 - Present
