A beginner’s guide to a career in data science

Jocelyn Kaylee Neo

 · July 07, 2020  · 07/07/2020

As a data-driven company, Revolut has always been focused on the value of data to our systems and processes. Mehroze Munawar, one of Singapore’s Data Analysts, describes data as “the internal compass of the organisation”. What she does is crucial to the company as a whole: observing, analysing, and informing on the direction that business teams may need to take. Building a career in data science may seem intimidating, but Mehroze is giving us the inside track with her top tips to get there.

1. Start with the basics

Transition into the world of data science fast by picking up technical skills in this order: focus on learning one programming language, dive into fundamental statistical theories, and contextualise with application. Make full use of free online resources like The Pudding, Linear Digressions and Data Elixir!

2. Work on personal passion projects  

If you’re deeply interested in the topic you’re working on, you’ll gain momentum faster - so get started and get creative. If you like music, connect to Spotify’s API and analyse data on your favourite artist. Or, if you're more interested in reading, parse your favorite book to learn natural language processing (NLP) basics.

3. Connect with online communities

Learn by reading other people’s codes, and analyse how someone else might be solving the same problem with very different coding structures. Consider the principles of design thinking as you’re doing so - the beauty of data science is that all roads lead to Rome.

4. Be inspired by the world around you

The world has no lack of problems, and data science can be a tool to proactively solve some of them. Think deeply about what problems you want to solve, and what good solutions might look like. From there, work your way backwards to mathematically model your problem.

5. Articulate the value of your work

Be a storyteller. Always create a narrative around your analysis to build context, and present its value in a way that inspires thought or action from others. Some data scientists may argue that this is the most important aspect of their work.

6. Take a leap of faith

Work silently, but offer your work for public feedback. Build a portfolio, share it with your peers/mentors, and take on their feedback. Every practice try is progress, so keep going. When you feel ready, apply for a data science career. Your new adventure is just getting started!

If it’s a role at Revolut that you’re after, you can check out all our open roles here.