Graduate Data Scientist

Wise is a global technology company, building the best way to move and manage the world's money.

Job Description

How you'll contribute to our team of data scientists:

• Help take Wise to the next level as we scale to impact hundreds of millions more customers.
• Work directly on projects that impact our customers and will help us prioritize the most significant improvements to our products with their convenience and trust in mind.
• Participate in building industry-proven machine learning based solutions and find opportunities to experiment with state-of-the-art algorithms.

This role will give you the opportunity to:

• Choose your path to impact. We believe people do great things when they can act autonomously. So, instead of being told what to do, you'll work with your team to create a vision of your own. You can always gather feedback from smart, curious people across Wise, but you'll have the freedom to make your own calls.
• Be flexible in how and where you work. We understand everyone needs a little something different - so we'll do our best to make it happen.
• Travel to work with our teams in different locations. You'll also meet various partners and organisations when needed.
• Inspire teams with your ideas, knowledge and self-starting attitude.

In your first 6 months:

• You'll onboard remotely and spend some time understanding your team and tribe's vision. Once you know this, you'll better understand how you can contribute.
• Understand the Wise domain.
• Understand the problems your team are solving.
• Understand how data science works at Wise and what each team and tribe does. From Marketing, to Treasury and Fraud teams - there are lots! Don't worry, we'll help you get acquainted.
• Understand the tech culture, the detail of the tech stack and how we build stuff. We work in autonomous teams, on different stacks so you'll need to understand the details.
• We're big on planning. You'll go through two quarterly plan cycles and get to propose your own ideas to take your product further.

Qualifications

What does it take? These things are a must:

• You are graduating in 2026 or did in 2025 from a Bachelors or Masters degree. This might be in Computer Science, Mathematics, or any other STEM subject.
• You are able to start a full-time graduate job on 7 September 2026.
• Knowledge of computer science and machine learning fundamentals including data structures, algorithms, data analysis, linear algebra, and statistics.
• Understanding principles of machine learning.
• You should have a good command of Python 3 and SQL and be familiar with major data analysis and ML frameworks such as Pandas, Scikit-Learn, and MLFlow.
• A self-started side project(s) that you are proud to talk about.
• Great communication skills and the ability to articulate complex, technical concepts to a non-technical audience.
• Curious, keen to learn, and proactive by nature.
• You are open to and value feedback in order to improve.
• Eligible to work in the UK without sponsorship (unrestricted right to work).

And any of these would be great, but aren't essential:

• Experience in applying machine learning methods to real-world problems.
• Familiarity with Bayesian methods in machine learning.
• Familiarity with challenges of supervised ML on imbalanced data.
• Familiarity with Apache Spark or other distributed processing frameworks.
• Experience in applying causal inference and/or uplift modeling techniques.
• Experience in software development, from a previous internship.

Additional Information

What you get back:

• Stock options in one of the fastest growing European FinTechs.
• An annual self-development budget.
• Pet-friendly offices.
• Salary of £52,500 / year.
• Lots of team activities.
• A paid 6-week sabbatical leave after four years.

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.