Data Analyst Internship

Type: Intern
Region: London

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 40+ 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 8,000+ 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

If you’re in your penultimate year of study, this one’s for you. You’ll work with us for three months and get to know everything we do.

First, kick off with a few weeks of bootcamp, where we’ll prepare you to jump into work at Revolut with workshops, lectures, and practical exercises to start working on your skills. After a successful preparation, we’ll launch you into on-the-job training. In this stage, you’ll be face-to-face with tough challenges, problem-solving and tasks to own. 

About the team

We approach Data Science at Revolut the same way that we approach everything else. We take complex problems, and create extraordinary solutions that our customers love. Our Data Analysts aren’t kept in the background, doomed to never see the impact of their work. They’re some of our best and brightest problem solvers, deployed to the front-lines to work in Product Teams and deliver rock star solutions.

We’re looking for a superstar Data Analysts who don’t believe there’s a data task that can be too hard. From digging into our complex databases, looking for the root cause of a problem to designing their own solutions and writing their own code to implement them. In this process, they never stop learning, picking up new skills, and delivering value.

Up for the challenge? Get in touch.

What you’ll be doing

  • Building new analytical pieces for the new products we’re planning to launch (i.e. Dashboards and ETLs).
  • Increasing visibility in our sign-up process and operational funnels
  • Maintaining and improving the existing infrastructure in terms of ETLs and LookML code to make sure our data is accessible and easy to use
  • Collaborating with stakeholders from operations, growth, and product teams to improve our product, and discover new insights
  • Supporting business needs with ad-hoc data analysis, (e.g. interest rate sensitivity, salary incentive profitability, payments conversion rates, onboarding funnels)

What you’ll need

  • Studies in Computer Science, Maths, Physics or a similar field
  • Great skills with Python, SQL, LookML, or other programming languages
  • Evidence of strong mathematical and statistics knowledge
  • A portfolio of multiple coding side projects or open source contributions
  • A proactive attitude
  • A love for problem-solving
  • Fluency in English
  • To be a quick learner
  • Ambitious and results-driven personality
  • Excellent communication and organisational skills
  • To feel comfortable working as part of a team in a fast-paced environment

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.

Job Overview
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