What excites me most about quantitative finance is that the problems never stop being interesting. I'm Tom, an MSCF student at Carnegie Mellon with a Bachelor of Mathematics in Computer Science and Statistics from the University of Waterloo, where I graduated with a 3.92 GPA and a perfect GRE Quant score. My experience spans the full stack of quantitative work. At BMO Capital Markets, I built algorithmic pricing frameworks and pre-trading validation systems that meaningfully reduced errors and improved trade readiness. At Boosted.AI, I developed AI-driven infrastructure that cut response latency by 40% using semantic caching and vector search. In my own research, I've built a multivariate Hawkes process simulator for limit order book dynamics and a statistical arbitrage backtester to test out ideas. I hold a CFA Level 1 and bring a perspective shaped by working across markets, software engineering, and machine learning. I'm drawn to roles in quantitative research and systematic trading where curiosity and rigor are equally valued. I'd love to connect virtually or in person to explore how my background can contribute to your team from day one! 听
