Aspiring Quantitative Researcher / Algorithmic Trader / Pricing Structurer
Open to graduate internship positions in May 2027
I am an engineering student in my final year at ENSAE Paris and École des Mines, specialising in statistics, finance and machine learning.
I work at the intersection of statistical learning, stochastic calculus for pricing and machine learning, aiming for a quantitative researcher or trader role on commodities markets, turning models into prices, and prices into decisions.
After a gap year shaped by quant and AI internships, I am gravitating toward finance, and energy & commodities in particular. That is what led me to build Boreas, a complete pricing app for weather derivatives, built on research I have run independently. Try the app here ↗ · more on the project ↓
AI Engineer @ Corpy&Co
A six-month internship in Tokyo, working within an international team for Japanese industrial clients, with weekly client meetings. I deployed machine learning solutions end to end. My main project was a hybrid OCR + VLM pipeline to digitize Japanese logistics delivery slips, covering detection, semantic extraction and geometric matching of structured tables.
Quantitative Researcher @ Natixis CIB
A six-month internship. I built a loan pricing model to monitor and mark-to-market Natixis' €100bn outstanding credit portfolio, and engineered a regression-based method to proxy CDS curves for illiquid, unquoted counterparties. I delivered the full pricing and curve-adjustment pipeline in C#, with regression diagnostics feeding the desk's daily mark-to-market and decision-support tools.
Research Assistant @ Milliman
A part-time academic-industry project exploring Federated Learning applied to insurance. I implemented federated regression models for automobile risk prediction and evaluated their performance. The full implementation is on GitHub. Supervised by François Hu (Head of R&D AI Lab) and Fallou Niakh (PhD in Actuarial Mathematics).
Data Scientist @ BPCE
I developed computer vision algorithms to extract data from unstructured PDFs through OCR and object detection, improving file-processing efficiency by 60% and saving managers thirty minutes a day. I also designed NLP models to streamline financial document management through clustering and classification.
A 5-month self-directed quantitative research project (2026), taking temperature models from weather derivatives to commodity trading.
Part 1 · Weather-derivative pricing
Stochastic and machine-learning temperature models for pricing weather derivatives, wrapped in Boreas, an end-to-end trading dashboard.
View the painting & full write-up ↗
Part 2 · Extension
A follow-up that links winter temperature anomalies to Henry Hub natural gas volatility, through a Schwartz–Smith state-space model and a weather-coupled GARCH.
View the painting & full write-up ↗
A couple of smaller side projects
Deep Learning · Video Analytics
Deep-learning detection and tracking of people and vehicles for video surveillance (2025).
Quant Portfolio · Pokémon Cards
A playful quant portfolio treating Pokémon cards as tradable assets (2023).
ENSAE Paris · IP Paris
MEng in Computational Finance, Statistics & Probability
Ranked #2 worldwide for quant-finance placements per capita (topQuantUnis), and a leading feeder into trading firms and hedge funds.
Institut Polytechnique de Paris
Institute of Science & Technology
Ranked #41 worldwide and #2 in France (QS 2026), grouping six of the country's leading engineering schools.
Seoul National University · SNU
Department of Statistics & Computer Science
South Korea's leading university, ranked #31 worldwide (QS). One-year international exchange in statistics and computer science, taught in English.
Mines Saint-Étienne · Institut Mines-Télécom
MEng in Applied Mathematics & Market Physics
Applied mathematics and the physics of energy and commodity markets, alongside a Bachelor in Fundamental Mathematics (Jean-Monnet University).
Collège Stanislas
Classes préparatoires (CPGE)
Intensive program preparing for the entrance exams to the French engineering Grandes Écoles.
Whether it is an opportunity or a question about my background or my projects, my inbox is always open.