Guillaume
Data Scientist
Lausanne, Vaud, Switzerland
Summary
🤩
RockstarGuillaume is a data scientist based in Lausanne, Switzerland, with six years of hands-on experience building reproducible ML workflows and time series forecasting solutions. He contributes actively to open-source, notably improving documentation, examples, and CI/CD for the widely used darts library for time series forecasting and anomaly detection. His work emphasizes developer experience—refactoring install guides, fixing examples, and adding utilities to ease local reproducibility for RNN models. Comfortable across the full stack of model development and deployment, he combines practical engineering rigor with a focus on clear, usable documentation that accelerates adoption. Colleagues value his attention to reproducibility and the small but impactful improvements that make complex tools accessible.
5 years of coding experience
Github Skills (16)
forecasting10
machine-learning10
time-series10
forecast10
anomaly-detection10
python10
documentation9
jupyter-notebook9
github-ci8
git8
cicd8
githubaction-workflow8
pandas7
tensorflow6
numpy6
Programming languages (1)
Github contributions (3)
unit8co/darts
Jun 2020 - Jul 2020
A python library for user-friendly forecasting and anomaly detection on time series.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:9 commits, 15 PRs, 34 pushes in 19 days
Contributions summary:Guillaume primarily focused on improving the project's documentation and examples, especially the README.md file. They refactored install guides, fixed example code, and added content to showcase the project's capabilities for time series forecasting and anomaly detection. They also implemented a reproducibility feature for RNN models and updated notebook examples and added utilities to fix python path locally. Further contributions included the addition of CI/CD enhancements and coverage reports.
forecastingpython-libraryanomalypythontime-series-analysis
guillaumeraille/darts
Jun 2020 - Jun 2020
A python library for easy manipulation and forecasting of time series.
Contributions:5 pushes, 1 branch in 3 days
forecastingmanipulationpython-librarypythontime-series-analysis
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