Ryan Kinnear
Member Of Technical Staff (Resident) at OpenAI
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolRyan Kinnear is a quantitative researcher and software engineer with 11 years of experience applying optimization, stochastic control, and machine learning to finance and real-time-bidding markets. Currently a Member of Technical Staff (Resident) at OpenAI, he previously developed production-grade control systems and transaction-cost-aware portfolio construction algorithms at hedge funds and in PhD research. His work blends rigorous convex-analysis and stochastic calculus with practical implementation in Python, C++, TensorFlow/PyTorch and high-performance simulation, with a knack for transforming auction problems into tractable convex programs. Notably his doctoral thesis connected auction-theoretic bidding strategies to precise models of market microstructure and metaorder impact, enabling direct application to trading systems. Based in New York, he combines deep theoretical insight with hands-on engineering to deliver low-latency, numerically robust solutions for high-frequency decision problems.
11 years of coding experience
3 years of employment as a software developer
Bachelor’s Degree, Electronics systems engineering, Academic Gold Medal (top 5% GPA), Bachelor’s Degree, Electronics systems engineering, Academic Gold Medal (top 5% GPA) at University of ReginaMaster’s Degree, Applied Sciences, Master’s Degree, Applied Sciences at University of Waterloo
Github Skills (58)
data-analysis10
notebook10
computer-algebra10
qt10
python10
jupyter10
data-science10
matplotlib10
statistics10
machine-learning10
ipython10
computer-algebra-system10
gtk10
science10
math9
Programming languages (7)
Github contributions (5)
RJTK/Levinson-Durbin-Recursion
Aug 2016 - Jul 2019
Contributions:45 commits, 32 pushes, 1 branch in 2 years 11 months
RJTK/rjtk.github.io
Feb 2023 - Mar 2023
Contributions:10 commits, 20 pushes, 1 branch in 1 month
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