Sylvain Marie
Research Engineer - IoT Analytics at Schneider Electric
Greater Grenoble Metropolitan Area France
Summary
🤩
Rockstar🎓
Top SchoolSylvain Marie is a research engineer specializing in IoT analytics with a decade of experience building cloud-native, distributed systems and production analytics for energy and industrial domains. Trained as a mathematician and physicist (Supelec, UCL), he blends rigorous theory—published research and three patents—with pragmatic delivery, having led prototypes to product and managed externally funded projects and technology transfers. At Schneider Electric he architects analytics platforms, migrates services to Python, supervises PhD work, and delivered asset-monitoring solutions now in production. An active open-source contributor, he has improved core ML and data libraries such as scikit-learn and pandas, fixing numerical stability and datetime performance issues. Comfortable from low-level electronics and control to Bayesian ML and DevOps, he runs creative IP sessions and mentors small agile teams. Sylvain’s unusual mix of deep theoretical instincts and hands-on “lead by example” engineering makes him a fast learner for new scientific challenges like quantum computing or learning robots.
10 years of coding experience
11 years of employment as a software developer
Ingénieur, BSc, Engineering (Mathematics, Electronics, Signal Processing, Computer Science, Control Theory, ...), Ingénieur, BSc, Engineering (Mathematics, Electronics, Signal Processing, Computer Science, Control Theory, ...) at École Supérieure d'Électricité / SupelecClasses préparatoires PCSI, PSI*, Mathematics, Physics, Chemistry, Engineering, Classes préparatoires PCSI, PSI*, Mathematics, Physics, Chemistry, Engineering at Lycée La Martinière Monplaisir, Lyon, FranceBaccalauréat Scientifique, Sciences, Mention AB, Baccalauréat Scientifique, Sciences, Mention AB at Lycée Blaise Pascal, Charbonnières, FranceUniversity College London
Stackoverflow
4,828reputation
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134answers
6questions
decorator
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pytest
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python
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Github Skills (33)
datetime10
python10
data-science10
scikit10
pandas10
machine-learning10
datetimes10
numpy10
dates10
scikit-learn10
data-analysis10
testing9
matrix-decomposition9
pytest9
text-formatting9
Programming languages (14)
Github contributions (5)
scikit-learn/scikit-learn
Mar 2019 - Jan 2022
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:79 reviews, 9 commits, 12 PRs in 2 years 10 months
Contributions summary:Sylvain primarily contributed to the `scikit-learn` project by fixing and enhancing the `KernelPCA` implementation, specifically addressing issues related to zero eigenvalues and numerical stability. They also improved the random number generation in the SVM and Liblinear solvers to fix convergence issues on Windows targets. Their work included bug fixes, code optimization, and incorporating new features like the "Randomized SVD" solver option. The user also addressed a floating-point precision issue related to eigenvalues.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
pandas-dev/pandas
Jan 2022 - Sep 2022
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:110 reviews, 6 commits, 9 PRs in 8 months
Contributions summary:Sylvain primarily contributed to improving the pandas library, focusing on datetime-related functionalities. Their work involved refining the `to_datetime` function, enhancing docstrings, and implementing return type hints. They also addressed formatting issues within the `Period` and `PeriodIndex` classes and optimized date/time string formatting routines. Furthermore, they contributed to improving the performance of the `period_format` function.
pythondatalabeled-datamanipulationdataframes
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