- Conducting Data Analysis for a variety of projects within the Office of Equity, Diversity, and Inclusion (EDI) and Dr. Melody Schiaffino’s research lab (Schiaffino Lab)- Utilized Microsoft Excel to manipulate and query electronic medical records- Utilized Python (MatPlotLib, Pandas, NumPy, SciKit Learn) to clean, manipulate, and analyze medical record data

Responsibilities- Collaborated with Professor Xin Wang to evaluate and quantify the performance improvements and efficiency gains achieved by the newly proposed clustered coefficient logistic regression model- Conducted extensive exploratory data analysis on datasets containing over 100,000 observations, extracting meaningful insights and identifying key patterns and trends- Developed and implemented regression models in R to predict response variables, effectively leveraging statistical techniques to provide accurate predictions- Utilized machine learning algorithms and proposed statistical models to identify distinct clusters within regression coefficient data, enabling enhanced understanding of underlying patterns and relationships