Data Scientist (Risk)

About Revolut

People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 70+ million customers get more from their money every day.

As we continue our lightning-fast growth,‌ 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work™. So far, we have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.

About The Role

Our Data Science team solves complex problems with smart, practical solutions. Data Scientists and Analysts work directly with product teams to uncover insights, guide decisions, and improve how customers experience Revolut. They do this by delivering smart, scalable solutions that move the business forward.

We’re looking for a Data Scientist who'll help us with effective assessment and management of risk by developing policies, methodologies, models, and systems for risk quantification, reporting, and monitoring.

Up to shape what's next in finance? Let's get in touch.

What You’ll Be Doing

• Developing and maintaining methodologies and policies for crypto risk 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
• 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, computer science, or quantitative finance
• 3+ years of experience in quantitative risk, financial engineering, or similar roles within trading, crypto, or fintech environments
• Knowledge of margin trading mechanics, derivatives pricing models, and liquidation/liquidity risk management
• Experience 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 + SQL skills for large-scale data analysis
• Familiarity with high-frequency datasets, and the ability to work well in fast-paced, real-time risk environments