I'm a business analyst who likes taking a messy question, finding the right data, and making the answer useful. I've spent more than 10 years in operations, finance, and business intelligence. Now I'm bringing that same curiosity to healthcare and biotech data as I work toward my master's in bioinformatics data science.
My work has taken me from running multi-location operations to building dashboards and reporting for large organizations. At Urban Economics, I analyze market and financial data for commercial real estate decisions.
At Compass Group USA's E15 team, I helped turn more than 6 billion operational records into a 14-million-row dataset for six dashboards. I'm working toward an M.S. in Bioinformatics Data Science at the University of Delaware, and I'm interested in bringing my analytics experience into healthcare or biotech.
Built and compared seven supervised ML models — Decision Tree through Deep Neural Network — on 5,888 clinical patient records to predict heart failure outcomes. Evaluated tradeoffs between accuracy (95.3% DNN) and interpretability (Random Forest feature importance) in a clinical context.
Applied a multi-method bioinformatics pipeline to characterize an unannotated bacteriophage protein — using PSI-BLAST homology search, HHpred remote homology detection, AlphaFold2 structural prediction, and literature synthesis to build a convergent case for functional assignment.
I'm currently open to data science and analytics roles, particularly in product-facing environments. Feel free to reach out directly.