LinkedIn Profile Successful musical performances require quick reactions, improvisational ability, pattern recognition, and the confidence to perform every day. When discovering new trends from large datasets through stochastic systems, machine learning, and regression analysis, I rely on these same skills. During my time in undergraduate studies, I gravitated towards both mathematics and economics to base my studies, but my interest in probability and statistical theory helped earn me a Bachelor’s Degree in Statistics and Data Science. Throughout college, I worked as a supplemental instructor for introductory calculus, sharpening my communication and public speaking. My love for finance did not start until after an internship with KeyBank. I’ve applied my knowledge extensively outside of the classroom. I utilized Python and SQL to create a decision tree model for credit card applications, and used those same tools to backtest and forecast extensions of a CCAR model. I used SQL and PowerBi to help an infrastructure equity firm recreate foundational dashboards while transitioning between data sources, and used R’s machine learning algorithms to create a PCA-driven index regression to find connected entry and exit rationales for an entrepreneurial survey. I have taken my work across oceans, and have gained an appreciation for financial markets both domestically and worldwide. I joined CMU MSCF to be able to unify and broaden my studies, to gain more experience in financial data science, and to ultimately pursue a career in quantitative research or trading. Outside of school, I am a bass guitarist and photographer.
