I am an M1 Actuarial Science student at Le Mans University, within the Institut du Risque et de l'Assurance, pursuing a double degree with the Data Science engineering programme at ESPRIT.
I completed my fourth year at ESPRIT with 17.02/20, ranked first in my class. My work connects actuarial questions with statistical validation and reproducible software. At M1 level, I am building breadth across pricing, reserving, mortality and model validation before choosing a specialization.
Available for a five-month M1 actuarial internship from April 2027. I remain open across actuarial domains.
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A released Python package for evaluating actuarial predictions across calibration, discrimination, uncertainty, monitoring and financial consequences. Documentation · PyPI · Source |
A reproducible comparison of classical, statistical, machine-learning and neural reserving methods under a common rolling-valuation protocol. |
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A working-paper project comparing classical, neural and hybrid mortality models through rolling-origin validation and an actuarial liability case study. |
An R-based study covering frequency-severity modelling, pure and commercial premiums, claims reserving and reinsurance under explicit assumptions. |
- RoadRisk Vision — a fork-based computer-vision project that produces exposure and driving-risk data for privacy-first telematics research. It does not claim to estimate insurance premiums or claims.
- Mortality, longevity and annuity pricing — an academic team project connecting mortality forecasting, survival probabilities and annuity valuation in R.
- Actuarial modelling: pricing, claims reserving, mortality and longevity
- Validation: temporal validation, calibration, discrimination and uncertainty
- Engineering: reusable libraries, automated tests, CI and reproducible pipelines
- Creator and maintainer of ActEval.
- Contributor to chainladder-python: merged documentation contribution PR #1196.
