Lead Data Scientist - Treasury Markets Quant

\n Company Description\n

Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed.

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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.

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

Job Description\n

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.

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Your work will have a direct impact on Wise's mission and millions of our customers.

About the Role\n

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.

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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.

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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\n

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

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

What we’re looking for

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• 4+ years building and maintaining production Python systems
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• Strong experience with microservices, databases, and production infrastructure
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• Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)
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• Quantitative background—maths, physics, engineering or finance—you can read a model and reason about correctness
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• Experience with testing, monitoring, and debugging complex systems under load
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• A product mindset—you think about who uses your systems and why
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• Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers
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It’s a bonus if you are familiar with

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• FX or financial markets experience
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• Term structure modelling, stochastic calculus or Monte Carlo methods
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• Interest rate curve bootstrapping
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• Algorithmic execution experience
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• Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)
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We’re people without borders—without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in.

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Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you.

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And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under-represented demographic.

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