- Locations
- London
- Madrid, Spain
- United Kingdom
- Dublin, Ireland
- Kraków, Poland
- Vilnius, Lithuania
- Porto, Portugal
- Berlin, MD
- Last Published
- Dec. 4, 2024
- Sector
- Fintech
- Functions
- Product
- Data Science
Product Owner (Data Science)
Office: Dublin · Krakow · London · Madrid · Porto · Vilnius Remote: Ireland · Poland · Portugal · Romania · Spain · UKAbout 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 45+ 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 WorkTM. 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
We love data. We can’t get enough. It sits at the heart of everything Revolut does. We use it to build intelligent, real-time systems that personalise our product, tackle financial crime, automate reporting, track team performances, enhance customer experiences and so much more 📈
We approach Data Science at Revolut the same way that we approach everything else. We take complex problems and create extraordinary solutions for them. All with data. From onboarding flows to product launches, we use it to inform and delight 😁 We build things that we actually want to use ourselves, because if you don’t want it, the customer certainly won’t.
We are looking for next-level Data Scientists to climb aboard the rocket ship and shape the future of financial services apps. It’s a big task. But you won’t be doing it alone. You’ll be working with the strongest professionals in Product, Design, Data Science and Engineering on projects which have direct customer impact and drive our company forward ⏩
What you’ll be doing
- Producing machine learning and statistical models to identify trends in our existing customer base and drive lead sourcing focus
- Producing predictive models to identify and score high potential sales leads
- Testing and improving
- Conducting deep-dive analysis to really understand complex problems
What you'll need
- Previous experience in a Data Science or Machine Learning based role
- Previous experience owning a machine learning project end-to-end, from design to implementation and iteration
- Great skills with Python, SQL or other programming languages
- Hands on experience with Deep Learning related libs (e.g. TensorFlow, Keras, PyTorch)
- Knowledge of version control, model deployment, developer environments
- Evidence of strong mathematical & statistics knowledge
- Strong background / education in a quantitative discipline
- Provide insight and deliver measurable results for sophisticated products under ambiguous situations in a fast-paced environment
- BS/BA degree from a leading university/college a plus
Compensation range
- Vilnius: €6,100 - €8,100 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.