Job Opportunities in the Seedcamp Portfolio

About Revolut

People deserve more from their money. More visibility, more control, more freedom. And since 2015, Revolut has been on a mission to deliver just that. With an arsenal of awesome products that span spending, saving, travel, transfers, investing, exchanging and more, we've helped 45+ million customers get more from their money. And we're not done yet.

As we continue our lightning-fast growth,‌ two things are essential to continuing our success: our people and our culture. We've been officially certified as a Great Place to Work™ in recognition of our outstanding employee experience! So far, we have 10,000+ people working around the world, from our great offices or remotely, on our mission. And we're looking for more. We want brilliant people that love building great products, love redefining success, and love turning the complexity of a chaotic world into the simplicity of a beautiful solution.

About the role

We approach Data Science at Revolut the same way that we approach everything else – with class, logical thinking, and lots of style 😎 Let’s break it down: we take the most complex problems and create tailor-made solutions for our customers 🚀 If you’re thinking the Data team is kept in some sort of a secret den, doomed to never see the impact of their work, don’t worry - that’s not how we do things. They’re some of our best and brightest problem-solvers, deployed to the front lines to work in product teams and deliver rockstar solutions 🤘

We start with deep data analysis to understand our customers, their objectives and any issues they might have. We then use various data points and advanced machine learning algorithms, to come up with the best possible option for each client. We experiment, iterate, and build fully automated solutions, based on algorithms which self-improve with time.

We’re looking for next-level Data Scientists to board our FinTech rocket ship and shape the future of financial services apps. Phew! It’s a big task, but you won’t do it alone. 💪

You’ll be working with the toughest and most gifted professionals in Product, Design, Data Science and Engineering, on impactful projects that’ll make our company move forward ⏩

What you’ll be doing

• Building models for full Retail Credit lifecycle
• Improving existing algorithms and building new Proofs of Concept
• Delivering real impact to the product through rigorous data-driven solutions
• Researching and then delivering PoCs into data products
• Collaborating with product owners, engineers, and data scientists to continually solve complex data problems

What you'll need

• Experience working in a data science team of a credit institution
• A Bachelor's/Master's/PhD in STEM (Mathematics, Computer Science, Engineering)
• Excellent knowledge of data science tools, including, python coding, SQL and production tools
• A deep understanding of probability and statistics fundamentals
• A big-picture mindset to correctly diagnose problems, produce research, and discover solutions
• Excellent communication and collaboration skills to partner with Product Owners and business heads

Compensation range

• Vilnius: €5,500 - €6,500 gross monthly*
• Lithuania: €5,500 - €6,500 gross monthly*
• Other locations: Compensation will be discussed during the interview process

*Final compensation will be determined based on the candidate's qualifications, skills, and previous experience

Building a global financial super app isn’t enough. Our Revoluters are a priority, and that’s why in 2021 we launched our inaugural D&I Framework, designed to help us thrive and grow everyday. We're not just doing this because it's the right thing to do. We’re doing it because we know that seeking out diverse talent and creating an inclusive workplace is the way to create exceptional, innovative products and services for our customers. That’s why we encourage applications from people with diverse backgrounds and experiences to join this multicultural, hard-working team.

Refer to our Data Privacy Statement for Candidates for details on our data handling practices during your application.