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
How you’ll contribute to our team of data scientists:
- Help take Wise to the next level as we scale to impact 100’s of millions more customers
- You will 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
- 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 2027 or did in 2026 from 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 6 September 2027
- Knowledge of computer science and machine learning fundamentals, Python and SQL
- A self-started side project(s) that you are proud to talk about
- Curious, keen to learn and proactive by nature
- You are open to and value feedback in order to improve
- Eligible to work in London.
And any of these would be great, but aren’t essential:
- Experience in applying machine learning methods to real-world problems
- Familiarity with supervised ML
- Familiarity with Time Series Forecasting
- Familiarity with supervised LLM chat and workflow automation
- Familiarity with Computer Vision
- Familiarity with Bayesian Learning
- Familiarity with Causal Inference
- Familiarity with Recommender Systems
- Familiarity with Graphs and GNNs
- Familiarity with Reinforcement Learning
- Familiarity with Apache Spark or other distributed processing frameworks
- Experience in software development
Additional Information
What you get back (London):
- 🚀 Stock options in one of the fastest growing European FinTechs
- 💪 An annual self-development budget
- 🐶 Pet friendly offices
- 💸 Salary of £58,000 / 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.
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.