Senior Quantitative Treasury/ALM Risk Modelling & Analytics – Treasury
Ebury is a dynamic fintech company and a leader in forex derivatives for hedging, offering sophisticated solutions to clients worldwide.

Ebury Madrid Office – Hybrid: 4 days in the office, 1 day working from home per week.

What you’ll do

Assist in the development and implementation of advanced quantitative risk models, including liquidity risk simulations, VaR99 calculations, and portfolio correlation analysis.

Contribute to the simulation of balance sheet evolution and the development of multi‑entity, multi‑currency hedging strategies.

Support the mapping of interest rate risk through DV01 analysis and the automation of hedging strategies.

Participate in IFRS valuation and delta attribution projects, linking market impacts to revenue drivers.

Contribute to the refactoring and optimisation of our code using Python and SQL.

Assist in the analysis of pricing and revenue optimisation strategies.

Document and present quantitative findings to the team.





Brainstorm and contribute ideas to innovate current processes.

What you’ll need

+5 years of experience in quantitative analysis or programming.

Proficiency in Python (NumPy, Pandas) and SQL.

Experience in quantitative finance or data analysis would be a plus.

A strong passion for quantitative financial mathematics and quantitative analysis.

Creative and innovative thinking, with a desire to challenge existing methodologies.

Analytical and problem‑solving skills.

Communication, documentation and presentation skills with the ability to explain complex concepts clearly and concisely.

Curiosity and a drive to learn complex financial concepts.

Ability to work effectively in a collaborative team environment.

Confident communication in English, both written and spoken.

Open to candidates from diverse academic backgrounds, provided they demonstrate a strong interest and aptitude for quantitative finance and risk modelling.

Why Ebury?

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📌 Senior Quantitative Treasury (Madrid)
🏢 Ebury Group
📍 Madrid