Quantitative researcher focused on machine learning research, statistical learning, market microstructure, and high-performance research systems for systematic trading.
Experience
Garden Leave – New York, NY
Non-compete Garden Leave | Feb 2026 – Present
Summit Securities Group LLC – New York, NY
Quantitative Trader | Dec 2023 – Feb 2026
Senior Quantitative Researcher | Oct 2019 – Dec 2023
Quantitative Researcher | Jan 2018 – Oct 2019
Consulting
Correlation One Inc. – New York, NY
Consultant | Feb 2017 – Jan 2020
Research
Lysy, M., Zhu, F., Yates, B., & Labuda, A. (2022). Robust and Efficient Parametric Spectral Density Estimation for High-Throughput Data. Technometrics, 64(1), 30-51.
Yates, B. (2018). Bayesian Sample Size Determination for Single-Particle Tracking of Pathogens in Biological Fluids. Master’s Thesis.
Education
Columbia Business School
MBA – Finance
University of Waterloo
MMath – Statistics – 3.98 / 4.00 GPA
University of Waterloo
BASc – Nanoengineering & Mathematics – 3.90 / 4.00 GPA