I've always been drawn to the challenge of making decisions under uncertainty. Whether through statistical modeling, machine learning, or financial theory, I enjoy building quantitative models that transform complex data into actionable insights. I graduated from the University of Toronto with a Specialist in Mathematical Applications in Economics and Finance and a Major in Statistics. Through both academic research and industry experience, I developed a strong interest in applying quantitative methods to solve complex financial problems. My professional experiences have allowed me to apply these interests across investment management, capital markets, and banking. At Ontario Power Generation, I analyzed portfolio performance and supported investment decisions for a multi-billion-dollar pension fund. At CIBC, I developed quantitative analytics that improved capital and portfolio management. Most recently, at TD Bank, I built machine learning models to enhance credit risk prediction and streamlined model development workflows, demonstrating how advanced analytics can create measurable business value. Working across these different areas of finance has given me a broad perspective on how quantitative models support decision-making throughout the investment lifecycle. I'm pursuing a Master of Science in Computational Finance at Carnegie Mellon University to deepen my expertise in advanced quantitative methods and global financial markets. After graduation, I hope to pursue a career as a quantitative researcher, developing data-driven models that advance systematic investing and support better investment decisions. I'm always excited to connect, virtually or in person, to discuss quantitative finance and how my background can contribute to your team.
