Data Scientist – Risk Modelling & Analytics

About the role

Revolut is looking for a Data Scientist to join its Risk team. You will design, build and maintain quantitative models that assess liquidity, market derivative exposure and margin risk, helping the company make data‑driven decisions in a fast‑moving fintech environment.

Key responsibilities

• Develop and maintain methodologies and policies for liquidity and market‑derivative modelling.
• Build, enhance and operate the core risk engine, including margin models, leverage frameworks and liquidation logic.
• Design, calibrate and validate risk models such as VaR, Expected Shortfall, SPAN, CCP‑style IM/VM, stress tests and scenario simulations.
• Collaborate with Engineering to deploy risk methodologies into production and iteratively improve them based on market conditions.
• Automate analytic workflows for P&L attribution, daily risk reporting, short‑term investment performance and cash‑flow analysis.
• Prepare compliance documentation and present risk insights, exposures and recommendations to senior leadership.

Required profile

• Degree in Mathematics, Statistics, Financial Engineering, Machine Learning or Computer Science.
• 3+ years of experience in machine learning, financial engineering or related roles focused on liquidity or market derivatives.
• Strong knowledge of margin trading mechanics, derivatives pricing and liquidity‑risk management.
• Proficiency in quantitative modelling and time‑series methods (GARCH, ARIMA, stochastic calculus).

Required skills

• Advanced Python programming.
• SQL for large‑scale data analysis.
• Risk‑modeling techniques: VaR, Expected Shortfall, SPAN, CCP‑style IM/VM.
• Time‑series analysis: GARCH, ARIMA, stochastic calculus.
• Derivatives pricing and margin model development.

What we offer

• Opportunity to shape risk analytics in a high‑growth fintech.
• Collaborative environment with product and engineering teams.
• Access to large, real‑world financial datasets.