Florian Pinault
Scientific Python Developer Engineer at ECMWF
Bonn, North Rhine-Westphalia, Germany
Summary
👤
Senior🎓
Top SchoolFlorian Pinault is a Scientific Python Developer with a PhD in computer science and over 11 years of R&D experience spanning computational linguistics, satellite remote sensing, and now machine learning for meteorology and climate. He blends a strong mathematical foundation from École Normale Supérieure and UC Berkeley with practical engineering at ECMWF and Météo‑France to build robust, testable data pipelines and models. His background in probabilistic models and PDE-inspired thinking informs work on fluid mechanics and diffusion-style approaches to atmospheric problems. Previously he led NLU research and implemented POMDP-based dialogue systems, which gave him a rare perspective on sequential decision and uncertainty modeling transferable to forecasting. On GitHub he’s improved reproducibility for high-profile educational projects in ML for weather and climate by adding automated testing for Jupyter notebooks. Based in Bonn, he enjoys revealing simple mathematical structures behind complex physical and linguistic phenomena and turning them into reusable code.
11 years of coding experience
7 years of employment as a software developer
Statistics, Statistics at University of California, BerkeleyMathematics and Computer Science, Mathematics and Computer Science at Ecole normale supérieureUniversité Paris Sud (Paris XI) / University Paris XI
Github Skills (6)
jupyter-notebook10
pytest10
python10
testing10
machine-learning8
data-science8
Programming languages (7)
Github contributions (5)
ecmwf-projects/mooc-machine-learning-weather-climate
Jan 2023 - Mar 2023
Role in this project:
Test Automation Engineer & Data Scientist
Test Automation Engineer & Data ScientistContributions:56 commits, 7 PRs, 45 pushes in 2 months
Contributions summary:Florian implemented automated testing for Jupyter notebooks, ensuring the reproducibility and functionality of the code examples. They added a testing framework (likely pytest) and developed tests to validate notebook execution. Additionally, the user corrected a minor typo in a notebook and contributed new data handling notebooks. Their work focused on improving the quality and usability of the project's educational content related to machine learning for weather and climate.
ecmwf-lab/ecml-tools
Oct 2023 - Mar 2024
Contributions:6 releases, 3 PRs, 160 pushes in 4 months
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