Company DescriptionWise 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.Job DescriptionMore about our mission and what we offer.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 customersYou 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 ToChoose 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 callsBe flexible in how and where you work. We understand everyone needs a little something different - so we’ll do our best to make it happenTravel to work with our teams in different locations. You’ll also meet various partners and organisations when neededInspire teams with your ideas, knowledge and self-starting attitude In Your First 6 MonthsYou’ll onboard and spend some time understanding your team and tribe’s vision. Once you know this, you’ll better understand how you can contributeUnderstand the Wise domainUnderstand the problems your team are solvingUnderstand 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 acquaintedUnderstand 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 detailsWe’re big on planning. You’ll go through two quarterly plan cycles and get to propose your own ideas to take your product furtherQualificationsWhat does it take? These things are a must:You are graduating in 2026 or did in 2025 from Bachelors or Masters degree. This might be in Computer Science, Mathematics, or any other STEM subjectYou are able to start a full time graduate job on 7 September 2026Knowledge of computer science and machine learning fundamentals including data structures, algorithms, data analysis, linear algebra and statisticsUnderstanding principles of machine learningYou 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 MLFlowA self-started side project(s) that you are proud to talk aboutGreat communication skills and the ability to articulate complex, technical concepts to a non-technical audienceCurious, keen to learn and proactive by natureYou are open to and value feedback in order to improveEligible 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 problemsFamiliarity with Bayesian methods in machine learningFamiliarity with challenges of supervised ML on imbalanced dataFamiliarity with Apache Spark or other distributed processing frameworksExperience in applying causal inference and/or uplift modeling techniquesExperience in software development, from a previous internship Don’t worry we don’t expect you to know everything!Additional InformationWhat 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 activities️ 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.