Laurent Direr
Full-stack Developer at Belenos (Freelance)
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolLaurent Direr is a Paris-based full-stack developer with 11 years of experience helping early-stage SaaS teams ship robust, maintainable products. Trained as an applied mathematics engineer, he blends strong Python backend skills (Django, Flask, FastAPI) with modern front-end frameworks and operational tooling (Docker, Kubernetes, AWS) to deliver high-throughput APIs and reliable deployments. He has repeatedly taken small teams from prototype to production—hiring developers, designing interview processes, and instituting best practices that improve engineering efficiency. An active open-source contributor, he has improved scikit-learn’s HashingVectorizer and worked on warm-starting random forests, reflecting an interest in machine learning edge cases as well as product engineering. Colleagues value him not as a transient contractor but as an embedded teammate who prioritizes impact, code maintainability, and pragmatic decision-making.
11 years of coding experience
5 years of employment as a software developer
Ingénieur des Arts et Manufactures Option Mathématiques Appliquées et Entrepreneuriat, Ingénieur des Arts et Manufactures Option Mathématiques Appliquées et Entrepreneuriat at CentraleSupélecAndroid Developer Nanodegree Android development, Android Developer Nanodegree Android development at Udacity
French, German, English
Stackoverflow
6,696reputation
758kreached
48answers
7questions
scipy
top-5%
artificial-intelligence
top-1%
scikit-learn
top-1%
nlp
top-1%
python
top-1%
dictionary
top-5%
Github Skills (21)
artificial-intelligence10
python10
data-science10
scikit10
machine-learning10
scikit-learn10
nlp10
testing9
scipy9
dictionary9
numpy8
data-analysis7
decision-tree6
random-forest6
cross-validation6
Programming languages (9)
Github contributions (5)
scikit-learn/scikit-learn
Jul 2014 - Jun 2017
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:17 commits, 3 PRs, 6 comments in 2 years 11 months
Contributions summary:Laurent primarily contributed to the `scikit-learn` repository by addressing issues related to the `HashingVectorizer` class. Their work involved correcting typos in docstrings, raising and handling exceptions for invalid input (specifically `np.nan`), and adding tests to validate the correct behavior of the `HashingVectorizer` with `np.nan` inputs. Further contributions include fixes to the documentation and refactoring of existing tests. The user also contributed to the introduction of warm start to random forests.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
ldirer/deploy-app-docker
Feb 2018 - Jan 2022
Contributions:26 commits, 5 pushes, 2 branches in 3 years 11 months
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