Junior Data Scientist
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About Revolut
People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 65+ million customers get more from their money every day.
As we continue our lightning-fast growth, 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work™. So far, we have 10,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.
About the role
Our Data Science team solves complex problems with smart, practical solutions. Data Scientists and Analysts work directly with product teams to uncover insights, guide decisions, and improve how customers experience Revolut. They do this by delivering smart, scalable solutions that move the business forward.
We’re looking for Data Scientists to help us shape the future of financial services. It’s a challenging task, but you’ll be part of a strong and supportive team.
You’ll be collaborating with experienced professionals in Product, Design, Data Science, and Engineering on impactful projects that drive our company’s growth.
Up to shape what's next in finance? Let's get in touch.
What you’ll be doing
- Improving existing algorithms
- Building new PoCs
- Delivering data-driven solutions to enhance product performance
- Researching and developing PoCs into scalable data products
- Collaborating with product owners, engineers and data scientists to continually solve complex data problems
What you’ll need
- Experience building and leading a data science team within a scaling organisation
- Bachelor's/Master's/PhD in STEM (Mathematics, Computer Science, Engineering)
- Solid knowledge of data science tools including Python, SQL and production frameworks
- Demonstrated knowledge of probability and statistics fundamentals
- The ability to think strategically and diagnose problems accurately
- Experience productionising research into scalable solutions