Driven to discover and determined to contribute, I am here to make a difference in quantitative finance. I earned a B.S. in Statistics from the University of Minnesota. Throughout my undergraduate studies, I strengthened my ability to apply quantitative models to real-world problems, including constructing three classifiers for credit default prediction. During my quantitative research internship, I developed and backtested trading strategies for Rebar futures in Python. I introduced statistical factor evaluation and machine learning to improve signal validity and risk control. During my asset management internship, I used time-series models to forecast pulp price trends and inform analysis of market dynamics. These experiences strengthened my interest in quantitative finance, which emphasizes iterative problem-solving and critical thinking. Beyond academics and work, I volunteered as a shift leader at Open Arms of Minnesota, where I prepared and delivered medically tailored meals to people with serious illnesses. Collaborating with people from diverse backgrounds strengthened my teamwork and leadership skills. I aim to pursue a career in quantitative research within asset management, using advanced models to generate rigorous investment insights and improve portfolio performance. I'm available to meet with you virtually or in person at our mutual convenience.
