Thomas Grivaz
Quantitative Trader
Geneva, Geneva, Switzerland
Summary
👤
Senior🎓
Top SchoolThomas Grivaz is a quantitative trader and data scientist based in Geneva with a decade of experience applying machine learning, deep learning and NLP to systematic trading and investment research. He has led end-to-end ML production at Credit Suisse and developed alpha signals and portfolio implementations across equities, futures and FX for hedge funds and proprietary trading firms. At SILEX and HTTS he managed long-only and market-neutral strategies, and now drives quantitative trading at Wilmar International, combining alternative data with novel models to improve investment decisions. His EPFL data-science background and a history of acoustic-event and NLP projects reflect a strong experimental bent—he publishes personal projects and code publicly, signaling a practice of reproducible, research-driven engineering.
10 years of coding experience
5 years of employment as a software developer
Master of Science (M.Sc.) Communication Systems - Specialization in Data Science, Master of Science (M.Sc.) Communication Systems - Specialization in Data Science at EPFL
Github Skills (12)
dplyr8
sparklyr8
trading7
r7
ide6
apache-spark6
spark6
machine-learning6
artificial-intelligence6
reinforcement-learning6
livy6
apache4
Programming languages (3)
Github contributions (5)
ThomasGrivaz/ai-for-trading
Sep 2018 - Jul 2019
code repository for Udacity nanodegree Artificial Intelligence for Trading
Contributions:15 commits, 10 pushes, 1 branch in 10 months
nanodegreeudacityreinforcement-learningartificialmachine-learning
ThomasGrivaz/reinforcement-learning
Oct 2018 - Jun 2019
Contributions:6 commits, 4 pushes, 1 branch in 8 months
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