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 DescriptionWe’re looking for a Lead Data Scientist to join our Pricing team in London.
This is a rare chance to shape how Wise prices cross-border money transfers — using data, machine learning and experimentation to keep pushing prices down while staying sustainable. What you build will have a direct impact on Wise’s mission and the millions of customers who rely on us for fair, transparent pricing
About the Role:
We are seeking a skilled and detail-oriented Data Scientist to help us develop a data-driven approach to pricing strategy and execution in a highly competitive remittance market.
As part of this team, you will leverage advanced analytics, machine learning, causal inference and robust experimentation to help Wise push price down, deepen our understanding of customers, and maintain a competitive edge. You will partner closely with the Pricing analytics and engineering teams, Pricing Product, FP&A, Commercial Directors and senior leadership — turning complex data into pricing decisions that move the business.
Here’s how you’ll be contributing:
Pricing Experimentation Framework
Design, build and run a robust framework for testing pricing structures, fee levels and promotional offers across corridors and customer segments.
Define key metrics, significance levels and reporting; apply causal inference to isolate the true impact of price changes.
Automate reporting and insight generation so pricing hypotheses can be tested scientifically and at scale.
Price Elasticity & Revenue Modelling
Partner with the Growth team to adapt price-elasticity insights into the core repricing framework.
Forecast the impact of price changes on demand, volume and revenue, and quantify the trade-offs.
Optimise pricing for different segments based on their sensitivity, and validate predictions against experimental data.
Automation & Data Infrastructure
Build data pipelines and monitoring that make accurate, timely pricing data accessible.
Reduce manual effort in pricing analysis and monitoring through automation.
Ensure data integrity through robust validation, and share best practices across the team.
Customer Contact Analysis
Apply machine learning to classify and analyse pricing-related customer support contacts (tickets, chats, calls).
Surface common pain points and confusion (e.g. “fee too high”, “confusing fee structure”) and emerging concerns.
Provide actionable insights to Product and Operations to reduce friction and simplify fee structures.
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.
Skills Required
- Advanced analytics experience
- Machine learning experience
- Causal inference expertise
- Pricing experimentation and experimental design experience
- Price elasticity and revenue modeling experience
- Data pipeline and monitoring experience
Wise Compensation & Benefits Highlights
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Equity Value & Accessibility — Equity is broadly accessible through RSUs granted to all employees in addition to salary, aligning rewards with company performance. This company‑wide ownership stance is consistently highlighted in the benefits descriptions.
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Leave & Time Off Breadth — Paid time off is notably generous, with a global minimum of 33 days and 36 days listed for U.S. locations. After four years, a six‑week paid sabbatical plus a £1,000 stipend further strengthens time‑away benefits.
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Wellbeing & Lifestyle Benefits — Lifestyle support includes work‑from‑anywhere for up to 90 days per year after six months, flexible working principles, and a 24/7 Employee Assistance Program. Extras like three annual “Me Days” and a professional‑development allowance add quality‑of‑life value.
Wise Insights
What We Do
Wise is a global technology company, building the best way to move and manage the world's money. With Wise Account and Wise Business, people and businesses can hold 40 currencies, move money between countries and spend money abroad. Large companies and banks use Wise technology too; an entirely new network for the world's money. Launched in 2011, Wise is one of the world’s fastest growing, profitable tech companies. In fiscal year 2025, Wise supported around 15.6 million people and businesses, processing over $185 billion in cross-border transactions and saving customers around $2.6 billion.
Why Work With Us
We’re truly global in who we are, how we work, and how we build. Everything we do is centred around creating a world of money that’s fast, easy, fair. And open to all. Everyone who works here owns a piece of Wise, from the work they do, to the stock they hold.
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Wise Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We expect new joiners in the office most days to build connections and learn from colleagues for their first six months. After that, most Wisers split their working week between the office and home, typically coming in at least 12 times a month.
