Career · Awards · Service

Experience

Moving between industry data science and academic research, and currently doing both at once.

Download the CV

  1. Since 2026

    Associate Professor in AI and Actuarial Science

    ISFA, Université Claude Bernard Lyon 1 · Lyon

    Teaching and research at the Institut de Science Financière et d'Assurances, at the meeting point of artificial intelligence and actuarial science.

    • Research on trustworthy AI and statistical learning for insurance.
    • Lecturing on data science and actuarial machine learning in the MSc in Actuarial Science.
    • Supervising student research projects at ISFA and ENSEA Abidjan.

  2. Since 2024

    Head of the R&D AI Lab

    Milliman France · Paris

    Leading the AI Lab inside the R&D division of Alexandre Boumezoued, with a focus on generative AI and trustworthy AI for insurance and finance.

    • Set the research agenda for GenAI and trustworthy AI (fairness, interpretability, privacy).
    • Build and lead the team turning research prototypes into client-facing work.
    • Bridge academic collaborations and applied actuarial practice.

  3. 2022 to 2024

    Postdoctoral Researcher

    Université de Montréal, Department of Mathematics and Statistics · Montréal

    Affiliated with Mila through Algora Lab, working with Arthur Charpentier (UQAM) and Manuel Morales (UdeM) on fairness, insurance and NLP.

    • Optimal-transport approaches to fairness with multiple sensitive attributes (AAAI 2024, ECML-PKDD 2023).
    • Early Warning System for Infectious Diseases, part of the Mathematics for Public Health initiative.
    • ESG concept extraction for Canadian companies with Algora Lab, for sustainable finance.

  4. 2019 to 2022

    PhD in Machine Learning and Insurance

    Institut Polytechnique de Paris (CREST-ENSAE) · Palaiseau

    “Semi-supervised learning in insurance: fairness and labelling”, supervised by Caroline Hillairet and Romuald Elie.

    • Awarded best actuarial thesis in France (SCOR Prize 2022).
    • Designed learning systems that are accurate in prediction, cheap in labelling and fair by construction.
    • Published in JMLR, AAAI and ECML-PKDD.

  5. 2018 to 2022

    Data Scientist

    Société Générale Insurance, Datalab · Paris

    Four years of applied data science on textual data, model transparency and insurance scoring.

    • Deployed machine-learning scoring models for home (MRH) and motor insurance.
    • Led projects on online learning, semi-supervised learning, transparency in deep models and computer vision.
    • Built end-to-end ML orchestration with Git, MLflow, Kedro and CI/CD.

Recognition

Awards and coverage

Best actuarial thesis in France, 2022

SCOR Prize, awarded by the Institut des Actuaires for Semi-supervised learning in insurance: fairness and labelling.

Ceremony Thesis

Montreal AI Ethics Institute

Our AAAI 2024 paper, A sequentially fair mechanism for multiple sensitive attributes, was written up as a research summary by the Montreal AI Ethics Institute.

Read the summary The paper

Skills, in practice

Statistical and machine learning (fairness, semi-supervised methods, optimal transport), NLP and LLM systems including retrieval-augmented pipelines, and the engineering to ship them: Python, R, Git, MLflow, Kedro, CI/CD and automated testing. The work usually involves presenting the same result to a research seminar and to a risk committee, which are not the same conversation.

The CV has the detailed and current version.