David Bellot is a Vice President and quantitative strategist with 16 years of experience building low-latency, high-frequency trading systems and dozens of high-Sharpe signals deployed across global venues from NYSE and CME to HKEx and ASX. He combines deep probabilistic AI and Bayesian ML research (postdocs at INRIA and UC Berkeley) with hands-on C++ implementation of execution algorithms, market-impact models, and market/order-book simulators. He has led small PhD-level quant teams to deliver signal generation, execution optimization, pricing models and tick-data analytics, and still contributes to open-source C++ libraries such as Boost.uBlas. Based in Sydney, he has industry leadership experience at WorldQuant, Life Trading and Barclays and a track record of translating academic ML advances into production-grade HFT infrastructure. An unexpected strength is his blend of rigorous Bayesian research background with practical calibration using modern ML/AI to tune ultra-low-latency strategies.
16 years of coding experience
6 years of employment as a software developer
Postdoctoral Fellow Machine Learning, Postdoctoral Fellow Machine Learning at University of California, Berkeley
PhD Bayesian Machine Learning, PhD Bayesian Machine Learning at Université Henri Poincaré, Nancy 1
Contributions:261 commits, 17 PRs, 13 pushes in 9 years 3 months
Contributions summary:David's commits primarily focused on modifying and testing the `boostorg/ublas` library, specifically related to its vector components. The changes involve adding and testing comments in the source code, particularly within the `vector.hpp` file. The repeated modifications to the same file and the nature of the commit messages suggest a focus on code maintenance and testing of existing library features and doxygen documentation. The user appears to be contributing to the existing codebase by adding documentation and/or preparing the library for release.
Contributions:6 commits, 3 pushes, 1 comment in 4 years 7 months
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David Bellot - Vice President, Quantitative Strategist