Max Halford
Staff Data Scientist
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolMax Halford is a Staff Data Scientist based in Paris with 11 years of experience bridging applied mathematics, production ML, and open-source engineering. He has progressed from academic research and teaching to industry leadership—formerly Head of Data at Carbonfact and a course instructor at Toulouse School of Economics—now focusing on scalable data products and model-driven decisioning. A prolific contributor to ML libraries, he authored core algorithmic pieces in projects like eaopt (evolutionary optimization in Go) and improved online-ml/river’s online learning and pipeline capabilities, showing deep expertise in both Python and Go. His background in applied mathematics and a PhD-level research trajectory underpin a rigorous, test-first approach to modeling and numerical stability (e.g., careful fixes to PCA/Correspondence Analysis implementations). Colleagues rely on him to turn complex statistical ideas into production-ready code and metrics that survive real-world constraints and data drift.
11 years of coding experience
2 years of employment as a software developer
Master of Science (MSc) Applied Mathematics, Master of Science (MSc) Applied Mathematics at Université Paul Sabatier Toulouse IIIAssociate’s Degree Applied Mathematics, Associate’s Degree Applied Mathematics at Université Toulouse 1 Capitole
French, English, Spanish
Stackoverflow
11reputation
1kreached
1answer
2questions
Github Skills (28)
genetic-algorithm10
online-machine-learning10
python10
data-science10
multiple-selection10
feature-selection10
testing10
scikit10
pandas10
machine-learning10
pca10
evolutionary-algorithms10
numpy10
go10
ensembles10
Programming languages (10)
Github contributions (5)
online-ml/river
Jan 2019 - Jan 2023
🌊 Online machine learning in Python
Role in this project:
ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:15 releases, 362 reviews, 1623 commits in 4 years
Contributions summary:Max focused on implementing and improving online machine learning techniques within the `online-ml/river` project. They added multiple new features to the `Pipeline` class, including mini-batch learning support, new methods and tests. The user contributed to the development of new metrics, specifically for measuring the performance of the learning process. They also worked on various model selection, and also fixed several issues related to the handling of various tests.
stream-processingpythonstreaming-datadata-scienceonline-statistics
MaxHalford/eaopt
Jan 2016 - Apr 2021
:four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
Role in this project:Back-end Developer
Back-end DeveloperContributions:11 releases, 301 commits, 46 PRs in 5 years 3 months
Contributions summary:Max implemented core functionality for the evolutionary optimization library, as evidenced by commits focused on population and agent structure, evaluation functions, and crossover methods. The code changes indicate a focus on algorithm implementation, including defining parameters, initialization, and evolving algorithms. These changes highlight the user's expertise in the Go programming language and its application to machine learning and optimization tasks.
evolutionneuroevolutionleafevolutionary-optimizationdifferential
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