LinkedIn Profile Some of the most interesting problems in finance are computer science problems in disguise. During my studies at BITS Pilani, I enjoyed tackling complex computational challenges, but I became increasingly fascinated by problems where mathematics and data intersect with human behavior. That curiosity drew me toward financial markets, an environment where decision-making under uncertainty is both an intellectual challenge and a practical necessity. This interest led me to Goldman Sachs, where I spent the past two years working in interest rate risk analytics. In this role, I developed stress-testing models to measure and manage risk across large financial portfolios, gaining firsthand exposure to how sophisticated analytics influence decisions at scale. The experience sharpened my technical toolkit and taught me that the best models are the ones disciplined enough to be useful, not just elegant. I now want to bring this combination of computational rigor and economic intuition to quantitative research in rates and derivatives markets, where pricing models meet the messiness of real portfolios. As I begin the MSCF program at Carnegie Mellon, I am eager to connect with professionals and fellow students who share a passion for quantitative investing and systematic buy-side research.
