Search jobs

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

Data Science at Stripe is a vibrant community where data scientists and data analysts learn and grow together. The Treasury Finance Data Science team builds the models, risk frameworks, and decision tools behind how Stripe manages money at global scale: liquidity, funding, counterparty risk, and foreign exchange.

Stripe moves funds across 135+ currencies every day. That creates FX exposure from merchant flows, multi-currency balances, and entity funding. In this role, you'll be a thought partner and builder alongside Stripe's FX team. Together you'll develop the quantitative foundation for how Stripe measures, forecasts, and hedges FX exposure.

What you'll do

You'll be the senior quantitative lead for FX within Treasury Finance Data Science. You'll co-build with Treasury, the FX hedging team, Finance, and Engineering: shaping the research agenda, turning ideas into rigorous models, and building the systems that put those models to work. Data Science owns these systems. They produce the decision-critical outputs and analyses that the FX team and Treasury leadership rely on. This is a hands-on role. You'll design the methodology, write the code, and ship it into production.

Responsibilities

• Partner with the FX team to build and evolve FX risk measurement: exposure aggregation across entities and currencies, VaR / Expected Shortfall, stress testing, and scenario analysis
• Develop forecasting models for FX exposures and multi-currency cash flows. Quantify forecast uncertainty so it can inform hedge sizing and timing.
• Co-design hedge optimization and decision frameworks with the FX team that weigh hedge cost, residual risk, P&L volatility, and liquidity constraints
• Build ML and statistical systems for trading and risk (signal research, anomaly detection on flows, execution and cost analytics), and take them from prototype to production
• Own the production systems that generate decision-critical FX outputs, partnering with Engineering on reliability, SLAs, monitoring, alerting, and incident response for risk-critical workflows
• Partner deeply with Treasury Finance stakeholders to turn business questions into quantitative frameworks. Anticipate needs and help shape FX risk strategy rather than reacting to requests.