CV
Applied Mathematician · Building Reliable AI Systems for Regulated Domains
Applied mathematician building reliable, mathematically grounded AI systems for regulated environments. Core toolkit: Bayesian and frequentist inference, optimisation for ML, kernel methods, deep learning, signal processing.
Experience
Data Lead (interim)
CRCDC Guadeloupe, Saint-Martin, Saint-Barthélémy · 2026–present
Rebuilding the end-to-end data chain of a regulated public health cancer-screening organisation.
- System audit, pipeline automation, and data governance on sensitive regulated health data
- R-based statistical reporting for national regulating entities
Independent Consultant — AI Reliability, Statistical Modelling & EU AI Act Readiness
Freelance · 2025–present
Statistical modelling and AI reliability consulting for regulated environments.
- Public health data chain audit and automation, anomaly detection frameworks, model evaluation methodology
- Building toward EU AI Act readiness assessments for healthcare and financial services clients
Research Engineer (CDD)
IFP Energies Nouvelles & ONERA · 2023–2024
Uncertainty and sensitivity analysis for coupled multiphysics systems (electrical motors, propulsion).
- Variance-based sensitivity indices (Sobol) and kernel-based methods for high-dimensional input spaces
- Exited to pursue a broader mathematical research agenda in AI systems and probabilistic ML
Applied Mathematics Intern
EDF R&D · 2023
Bayesian calibration of physics models with uncertain inputs.
- Bayesian calibration of physical models with noisy data using Python and OpenTURNS
- MCMC sampling methods and exploration of unbiased parameter estimation via Markov-chain couplings
Data Analysis & Science Intern
Avicenne Hospital · 2022
Healthcare data analytics for patient management.
- Patient attendance data & trend analysis
- Development of interactive dashboards in R
Education
MSc Year 2 (M2 MASH), Mathematics & Machine Learning
Université PSL, Paris · 2022–2023
MSc Year 1 (M1 Statistiques), Applied Mathematics - Statistics
Université Paris-Dauphine, Paris · 2021–2022
BSc (Licence MEFA), Applied Mathematics, Economics & Finance minors
Université Paris-Dauphine, Paris · 2018–2021
French Scientific Baccalaureate (BAC S), Mathematics
Maîtrise de Massabielle, Pointe-à-Pitre · 2013–2016
Skills
Statistics & Inference
- Bayesian Inference
- Statistical Modelling
- Uncertainty Quantification
- Sensitivity Analysis
- Computational Statistics
- Time Series Analysis
Programming & Data Science
- R
- Python
- Git
- LaTeX
- Markdown
- Jupyter
Mathematics & Machine Learning
- Statistical Learning
- Deep Learning
- Optimisation
- Stochastic Processes
- Numerical Methods
Certificates
Oxford Machine Learning Summer School
OxML
Languages and interests
- French
- Native speaker
- English
- Fluent
- Sports
- Muay Thai, Bouldering
- Arts
- String Instruments