Mathilde Léval
Senior Data Scientist
Greater Paris Metropolitan Region France
Summary
🤩
Rockstar🎓
Top SchoolMathilde Léval is a Senior Data Scientist based in Greater Paris with five years’ experience building and scaling ML systems across insurance and talent platforms. She has led technical improvements and team onboarding at Shift Technology, developed NLP-driven job recommendation models and bias mitigation work at Cornerstone, and now applies that expertise at Sunrise. Hands-on in production engineering, she contributes to the popular open-source CodeCarbon project, improving accuracy of compute energy measurements by refactoring hardware-specific power estimations and adding RAPL-based CPU overrides. Comfortable across the stack, she combines applied math training from Imperial College and an engineering degree from École Supérieure d'Électricité with practical skills in Python, Scala/Spark, C# and MLOps. Colleagues describe her as a pragmatic problem-solver who translates research into reliable, observable products while keeping sustainability of compute in mind.
5 years of coding experience
8 years of employment as a software developer
Engineering degree, Cumulative GPA: 3.55, Engineering degree, Cumulative GPA: 3.55 at École Supérieure d'ÉlectricitéCPGE, MPSI-MP*, CPGE, MPSI-MP* at Lycée Saint-LouisMaster of Science (MSc), Applied Mathematics, Distinction, Master of Science (MSc), Applied Mathematics, Distinction at Imperial College London
French, English, Japanese, Spanish
Github Skills (9)
python10
system-integration10
integrations10
hardware-interface10
refactor9
refactoring9
testing8
git7
devops6
Programming languages (1)
Github contributions (5)
mlco2/codecarbon
Sep 2021 - Nov 2021
Track emissions from Compute and recommend ways to reduce their impact on the environment.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:2 reviews, 47 commits, 6 PRs in 1 month
Contributions summary:Mathilde primarily focused on enhancing the codebase related to measuring and tracking compute emissions. They refactored and moved power and energy-related calculations into specific hardware classes. The user implemented overrides for CPU measurements using RAPL files, improving the accuracy of energy consumption tracking. Furthermore, their contributions included refactoring and renaming functions, along with integrating recent changes to the master branch, demonstrating their involvement in project maintenance and updates.
pythondata-scienceemissionscarbon-emissionsrecommend
mathilde-leval/vitemadose
May 2021 - Jun 2022
Détection de créneaux de vaccination disponibles pour l'outil ViteMaDose
Contributions:24 pushes, 16 branches in 1 year 1 month
vaccinationoutilvite
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