Data Scientist (Risk)

Data Scientist (Risk)

Revolut

Multiple Locations

We’re looking for a Data Scientist who'll effectively assess and manage risk by developing policies, methodologies, models, and systems for risk quantification, reporting, and monitoring.

What you’ll be doing

• Developing and maintaining methodologies and policies for liquidity and market derivative modelling
• Delivering real impact to the product through rigorous data-driven solutions
• Building, enhancing, and maintaining the core risk engine, including margin models, leverage frameworks, and liquidation logic
• Developing and calibrating risk models across isolated/cross margin, partial/full liquidation, bankruptcy pricing, and future portfolio margining capabilities
• Collaborating with Engineering to deploy risk methodologies into production systems while iteratively improving models based on market conditions
• Automating advanced analytic workflows, including P&L attribution, daily risk reporting, short-term investment performance, and cash flow analysis
• Preparing documentation for compliance, and presenting risk insights, exposures, and recommendations to senior leadership

What you'll need

• A degree in mathematics, statistics, financial engineering, machine learning, or computer science
• 3+ years of experience in machine learning, financial engineering, or similar roles within liquidity or market derivatives
• Knowledge of margin trading mechanics, derivatives pricing models, and liquidation/liquidity risk management
• Expertise in building and validating risk and margin models (VaR, Expected Shortfall, SPAN, CCP-style IM/VM, stress tests, scenario simulations)
• Proficiency in quantitative modelling and time-series methods (GARCH, ARIMA, stochastic calculus), with advanced Python and SQL skills for large-scale data analysis
• Familiarity with high-frequency datasets, and the ability to work well in fast-paced risk environments

Nice to have

• Experience at a major financial institution, asset manager, or liquidity provider, or within a treasury or risk department (FTP, ALM, liquidity, IRRB, etc.)
• Exposure to market-making workflows and risks (inventory management, P&L drivers, spread optimisation, and internalisation strategies)
• Familiarity with regulatory and institutional risk frameworks (Basel III/IV, FRTB, SA-CCR, CCP margin methodologies)