Experience: 8 years · Data scientist, with a strong interest in DevOps · Python · NLP · MLOps · Data privacy · Ethical AI · Open-source
Built an automated classification pipeline for HR documents, all formats, from scratch.
Built up and led a team of 5 persons.
Set up the Machine Learning team at PeopleDoc.
Developed MLV-tools, an open-source MLOps toolkit for easy Machine Learning pipeline versioning.
Developed data-driven algorithms for connected cars.
Implemented the data pipeline from scratch, with a focus on code quality and reproducibility of results.
Designed the corporate data strategy to improve data gathering in the long term.
Developed a personalised coaching algorithm to improve driver safety and promote eco-driving.
Research and development on a rule inference engine (quality analysis on manufacturing processes).
Refactored legacy code, updated documentation and tests, improved rule intelligibility.
Improved predictive power of the rule engine using boosting techniques.
Added a prescriptive module for correcting poor quality outcomes.
6-month internship: Inference of gene regulatory networks from DNA chips data
Implemented in Python optimisation algorithms for Deep Neural Networks.