Bridging financial forensics with machine learning to detect, predict, and prevent fraud at scale.
Event study analyzing stock market reactions to corporate fraud disclosures using the Fama-French Three-Factor Model. Reveals abnormal returns and market timing patterns.
Logistic regression model predicting passenger survival using feature engineering and data preprocessing pipelines.
Exploratory analysis of DC metro ridership at university stations, examining weekday vs. holiday effects and seasonal trends.
Statistical analysis of career level's impact on salary in NYC job postings using multiple regression and hypothesis testing.
Identifying high-value skill bundles and salary relationships through labor market data mining.
Regression modeling of how audio features and genre relate to song energy levels in Spotify data.
American University · Kogod School of Business
Washington, DC · Machine Learning, Predictive Analytics, Financial Modeling, Data-Driven Decision Making
John Jay College of Criminal Justice, CUNY
New York, NY · Fraud Detection, Financial Crime Investigation, Forensic Accounting, Data Analysis
Association of Certified Fraud Examiners
One of the most rigorous anti-fraud credentials globally, awarded August 2025.
Association of Certified Fraud Examiners
Prestigious scholarship awarded to outstanding students in fraud examination, May 2024.
Microsoft
Advanced proficiency in Microsoft Excel, including data modeling and analysis tools. December 2021.
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