National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Scientist - Markets & FX (Quantitative Researcher)

Wise
London
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

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 life 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 .

Job Description

We are seeking a talented Markets Data Scientist (Quantitative researcher) with expertise in FX risk modelling to join our dynamic Treasury team. This role focuses on driving our FX risk and pricing models and optimising their impact on our trading strategies. 

Your work will have a direct impact on and millions of our customers.

As part of the team, you’ll be at the forefront of designing, implementing, and refining models that manage foreign exchange (FX) risk, optimising the effectiveness of hedging strategies, supporting pricing, and influencing decision-making processes across the organisation. Your mission is to help us assess and manage our risks in real time, and help us keep lowering our prices and keep our market risk capital requirements scalable.

Our FX team manages the risk on our GBP 105bn+ FX book and our GBP 15bn of customer assets.

Here’s how you’ll be contributing:

FX Risk modelling and analysis

Develop and maintain advanced FX risk models, leveraging cutting-edge quantitative techniques to assess and manage FX risks (scenario modelling, stress testing, BAU risk metrics)

Perform back-testing and calibration of models to ensure accuracy, robustness, and regulatory compliance.

Collaborate with engineering teams to implement models within the risk and trading platforms, ensuring scalability and operational efficiency.

Develop bespoke models and analyses in preparation for market stress events and new product launches

Customer-centric insights

Conduct in-depth quantitative analysis to support pricing strategies and deliver insights on FX impacts on customer portfolios and products.

Model customer behaviour under various FX and market scenarios, informing decisions that maximise customer value and minimise risk.

Proactively monitor and assess the customer impact of FX fluctuations, recommending risk mitigation strategies that align with customer needs and regulatory standards.

Collaborative strategy development

Work closely with FX dealers to integrate model findings into real-time risk management and FX hedging strategies underpinned by customer behaviour models across a multi-region portfolio of products and currencies, including many exotics.

Partner with product and operational teams to translate complex FX risk scenarios into actionable insights for customer-focused solutions.

Document and present model results and risk assessments to senior stakeholders, controllers and the Risk team (the second line of defence). Explain complex concepts and propose strategies that align with the company’s risk appetite and business objectives.

A bit about you: 

Strong Python knowledge. Ability to read through code, especially Java. Demonstrable experience collaborating with engineers.

Strong knowledge in at least a few of the following areas: statistics, machine learning, linear algebra, optimisation.

A good understanding of FX market fundamentals and risk management methods and techniques, including VaR/sVAR, EVT/ES, PFE, XFA and Monte Carlo methods. 

A strong product mindset with the ability to work in a cross-functional and cross-team environment;

Good communication skills and ability to get the point across to non-technical individuals;

Strong problem solving skills with the ability to help refine problem statements and figure out how to solve them.

Some extra skills that are great (but not essential):

Experience in interest rate and cashflow modelling, derivatives pricing (including exotic options), behavioural models

Real FX trading experience (especially with algorithms)

Experience with building and maintaining backtesting engines and quantifying backtesting output using standard industry metrics ( Sharpe, Sortino)

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 .

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

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.