Commodity markets, quantitatively. I build models that turn physical fundamentals into views on futures curves, spreads and regime shifts.

I'm currently a Quant Analyst Intern at Cargill in Geneva for the summer. In parallel, I'm pursuing my MSc in Data Science with a minor in Financial Engineering at EPFL, after a BSc in Computer Science and Engineering, also at EPFL.
My work focuses on quantitative modelling in commodity and power markets, translating physical fundamentals (S&D balances, storage, trade flows, inventories) into signals across futures curves, spreads and differentials.
Before Cargill, I completed a Quantitative Analyst internship at Pareto Economics in London, building commodity market signals from production data, refining throughputs and global trade flows to analyse supply and demand dynamics, market exposures and asset dependencies.
Previously, I served as President and Head of Sales at Junior Entreprise EPFL, Switzerland's largest student run consultancy, where I led a 35 person team. I personally closed CHF 430k in projects across finance, commodities and energy, and managed more than CHF 500k in total volume, driving 22% YoY revenue growth.
Outside of work, I'm interested in financial history and its links to global politics, classical and practical philosophy, horology and tennis.
Projects across European power markets, futures curve factors, commodity spreads and market regime detection.




When German renewables flood the grid, which neighbouring market reprices first?
Analysed cross border price transmission in European electricity markets using ENTSO-E data, 301k observations and 5 Central European bidding zones. Built an interactive view of how German renewable surplus and negative day ahead prices move together across neighbouring markets.
Happy to talk about commodity markets, models or project work.