Edouard d'Archimbaud
Kansas, France
Summary
🤩
Rockstar🎓
Top SchoolEdouard d'Archimbaud is a data-centric software engineer with 10 years of experience focusing on turning machine learning research into production-grade systems, currently championing training data platforms at Kili to accelerate enterprise AI. Trained in applied mathematics, machine learning and finance at École Polytechnique, ENS Cachan and Paris Dauphine, he blends rigorous quantitative skills with practical engineering to prioritize data quality and labelling workflows over model-only thinking. His open-source work includes back-end and quantitative-finance contributions to a well-regarded systematic trading repository, implementing robust backtests and integrating historical futures data for realistic strategy evaluation. Based in Kansas and rooted in French academia, he brings a rare mix of formal math training, production deployment experience, and hands-on quantitative trading engineering to help teams ship impactful AI systems.
10 years of coding experience
DEA, Mathematics (Machine Learning), DEA, Mathematics (Machine Learning) at École Normale Supérieure de CachanMathematics, Mathematics, Mathematics, Mathematics at Lycée Sainte GenevièveMaster, Applied Mathematics - Computer Science, Master, Applied Mathematics - Computer Science at Ecole polytechniqueDEA, Mathematics (Finance), DEA, Mathematics (Finance) at Université Paris DauphineBaccalaureat (mention TB), Mathematics, Baccalaureat (mention TB), Mathematics at Saint Jean Hulst
Github Skills (14)
pandas10
tradingview10
backtesting10
python10
trading10
algorithmic-trading10
quantitative-finance10
backtest10
data-analysis9
trading-algorithms9
clicking8
clickable8
oneclick8
onclick8
Programming languages (3)
Github contributions (5)
paperswithbacktest/awesome-systematic-trading
Feb 2022 - Jan 2023
A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.
Role in this project:
Back-end Developer & Quantitative Finance Engineer
Back-end Developer & Quantitative Finance EngineerContributions:6 reviews, 102 commits, 7 PRs in 11 months
Contributions summary:Edouard's primary contribution involves implementing and refining a buy-and-hold trading strategy, evidenced by extensive code changes to `buy_and_hold_strategy.py` and `.ipynb` files. They demonstrate proficiency in using backtesting engines, data loading, and performance analysis libraries like `pyfolio` and `empyrical`. The user has focused on integrating historical futures data and evaluating strategy performance, demonstrating experience in quantitative finance principles.
backtesting-trading-strategiesfuturesmarketsquantfinancefutures-market
edarchimbaud/awesome-data-centric-ai
Jan 2022 - Mar 2022
Contributions:15 commits, 15 pushes, 1 branch in 1 month
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