Data Analyst

• Selected for BioKind Analytics, a competitive student-led data analysis group at UVA, to collaborate with nonprofits on impactful data-driven projects. • Analyzing over $100,000 in donations using Python and R, automating the separation of monetary vs. asset donations, and improving data consistency by 40% through custom scripts and statistical modeling. • Developing machine learning models (Random Forest, XGBoost) in Python to predict high-value donors with 85% accuracy, and using time series analysis in R to forecast event-based revenue with a 5% MAPE.