Daniel Zhang

WORK HISTORY

EDUCATION

ABOUT DANIEL ZHANG

Hi, I’m Daniel! I hold a Master of Mathematics (MMath) in Statistics from the University of Waterloo, where I’m now continuing as a PhD candidate in Statistics. Born and raised in Toronto, I’m passionate about using machine learning and statistical modeling to generate insights, build interpretable systems, and support decision-making. I’ve interned across sectors—research, finance, and environmental tech—at the National Research Council, Intact Financial, TD Bank, and Blue Lion Labs. My work has ranged from machine learning research and federated learning to analytics strategy and building production-grade data pipelines. I’ve also conducted academic research in federated learning as part of the VIP Lab at Waterloo. I’m excited by problems at the intersection of statistical theory and practical impact, and I aim to continue growing as a machine learning researcher and data scientist. Outside of school, you can find me in the gym or on the badminton court. Interests: Machine Learning, Bayesian Inference, Interpretable AI, Federated Learning, Data Analytics, Spatial Statistics