Role details
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 our mission and what we offer .
Job Description
We'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 .