Lead Data Scientist - Treasury Markets Quant

Company Description Wise is a global technology company, building the best way to move and manage the world’s money.

Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.

For everyone, everywhere.

More about our mission and what we offer.

Job Description 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

Qualifications

What we’re looking for4+ years building and maintaining production Python systems

Strong experience with microservices, databases, and production infrastructure

Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness

Experience with testing, monitoring, and debugging complex systems under loadA product mindset - you think about who uses your systems and why Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers

It’s a bonus if you are familiar withFX or financial markets experience

Term structure modelling, stochastic calculus or Monte Carlo methods

Interest rate curve bootstrapping

Algorithmic execution experience

Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if…