Lead Data Scientist - Treasury Markets Quant

We are seeking a talented quantitative developer to join our Treasury Markets Data Science team. This role focuses on owning and operating the production infrastructure behind our FX pricing, risk, and trading systems with the opportunity to broaden the scope of work into traditional quant aspects. Your work will have a direct impact on Wise’s mission and millions of our customers. About

the Role

You'll join the Treasury Markets Data Science team, owning the quantitative infrastructure that powers how Wise manages FX risk across a USD 250bn+ in annual FX volume- serving everyone from retail customers sending money abroad to tier-1 banks via Wise Platform. The wider Treasury FX team includes quants, traders, analysts, product managers and engineers working together to price, hedge, manage and scale FX operations within Wise in real time. Within that, the Data Science team owns the quantitative platform:

We run a Python-first, production-grade quant platform: real-time curve construction, multi-instrument pricing, risk analytics, and trading strategy - all built and operated by the same team. Your primary focus is keeping these systems reliable, performant and well-engineered - while thinking deeply about how they serve customers and products. You'll also contribute to the quantitative models themselves as you grow into the domain. What you’ll own

• Python microservices that run quantitative models in production
• Monitoring, alerting, and reliability for real-time pricing and risk systems
• Shared quant libraries used across multiple services
• CI/CD pipelines, deployment and operational excellence
• Incident response and root cause analysis for production issues

Where you’ll grow

• Real-time curve construction (yield curves, FX forwards, vol surfaces)
• Pricing models for new instruments and products
• Trading strategy development and optimisation
• Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)
• Backtesting frameworks and model validation
• Customer behaviour modelling, pricing strategy and product launch support
• Collaborating with product teams to translate quantitative insights into customer-facing decisions