Data Scientist

Revolut
  • Post Date: October 6, 2024
  • 15376
  • Applications 0
  • Views 3
Job Overview

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 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 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

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 落

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

Improving existing algorithms and building new Proofs of ConceptDelivering real impact to the product through rigorous data-driven solutionsResearching and then delivering PoCs into data productsCollaborating with product owners, engineers and data scientists to continually solve complex data problems

What You’ll Need

Experience building and leading a significant data science team within a scaling organisationBachelor’s/Master’s/PhD in STEM (Mathematics, Computer Science, Engineering)Excellent knowledge of data science tools, including, python coding, SQL and production tools.Deep understanding of fundamentals of probability and statistics.Big picture thinking – correctly diagnosing problems and productionising research.Excellent communication and collaboration skills to partner with Product Owners and business heads

Nice to have

Advanced degree in a quantitative discipline (e.g., Masters or PhD)Strong experience with additional programming languages (such as: Java, Scala, C++…)Previous experience in anti fraud departmentsExperience working at a large tech company worth >$15BSchool/University Olympic medal competitions in: Physics, Maths, Economics or Programming

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.

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