Quantitative Researcher / Developer (Data Science) - Treasury FX

Qualifications

What we’re looking for

• 4+ years of relevant quantitative or engineering experience, with strong Python development skills.

• Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness.

• It’s 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.)

• 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.

• Experience taking quantitative work into production and owning its ongoing validation, monitoring and improvement.

For the Researcher track

• Strong experience in quantitative research or modelling in finance, with depth in an area such as pricing, forecasting, risk or trading.
• Ability to translate an open-ended financial problem into a quantitative model, choose appropriate statistical or numerical methods, and explain assumptions and limitations.
• Experience designing backtests and out-of-sample validation, accounting for data leakage, transaction costs and changing market conditions.

For the Developer track

• Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)

• Experience with testing, monitoring, and debugging complex systems under load

• Strong experience with microservices, databases, and production infrastructure

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.

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.

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

Additional Information

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

We're 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 it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

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 what we offer.

Job Description

We are seeking a quantitative researcher or quantitative developer to join our Treasury FX Data Science team. You will help build and operate the models and production systems behind FX pricing, risk and trading. Your work will have a direct impact on Wise's mission and millions of our customers.

About the Role

You'll join the Treasury FX Data Science team, helping own the quantitative models and production infrastructure that power how Wise manages FX risk across USD 250bn+ in annual FX volume - serving everyone from retail customers sending money abroad to tier-1 global investment 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 a Python-first, production-grade quant platform which provides multi-instrument pricing, product modelling/monitoring, risk analytics and trading strategies.

We're hiring for two complementary focus areas

• Quantitative Researcher: Bring deeper expertise in quantitative modelling to develop and improve pricing, forecasting, risk analytics and hedging methodology with rigorous backtesting and stakeholder engagement

• Quantitative Developer: Bring deeper expertise in quantitative engineering to develop and improve production services, shared quant libraries and engineering reliability. You are expected to

Your focus will reflect your strengths, with opportunities to contribute across both areas and broaden your expertise. We expect depth in one area, with a strong shared foundation in Python, quantitative reasoning and production ownership.

What you'll own

• A primary focus in either production quantitative engineering or applied quantitative modelling

• Python implementation of quantitative work from research or prototype through reliable production use

• Validation, backtesting and monitoring of model and service performance against realised outcomes

• Deployment, incident response, root-cause analysis and continuous improvement with stakeholders

• Shared quant libraries used across multiple services

• CI/CD pipelines, deployments and operational excellence

• Monitoring, alerting, and reliability for real-time pricing and risk systems

Where you'll grow

• Market data management and onboarding new pipelines..

• Designing new quant infrastructure and systems with the engineering team.

• Backtesting frameworks, model validation and risk modelling alongside the Risk team (VaR, stress testing, scenario analysis).

• Customer behaviour modelling, pricing strategy and product development.

• Collaborating with product teams to translate quantitative insights into customer-facing decisions