Lead Data Scientist (Quant) Treasury FX

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 Wises mission and millions of our customers.
 

About the Role: 

Youll 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. Youll also contribute to the quantitative models themselves as you grow into the domain.

What youll 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 youll 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 were looking for

• 4 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 load

• A 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

Its a bonus if you are familiar with

• FX 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.)

Were people without borders without judgement or prejudice too. We want to work with the best people no matter their background. So if youre passionate about learning new things and keen to join our mission youll fit right in.

Also qualifications arent that important to us. If youve got great experience and youre great at articulating your thinking wed like to hear from you.

And because we believe that diverse teams build better products wed especially love to hear from you if youre from an under-represented demographic

Additional Information :

For everyone everywhere. Were people building money without borders  without judgement or prejudice too. We believe teams are strongest when they are diverse equitable and inclusive.

Were proud to have a truly international team and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what its like to work at Wise visit .

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Remote Work :

No

Employment Type :

Full-time