Revolut - Data Scientist

A LITTLE ABOUT US 

From clunky apps to hidden fees, banking as we know it is broken. So we decided to build a company from the ground that would challenge the bigger players and reinvent how people interact with their money - for the better.

Traditional banks are slow and expensive. Realistically, you’re nothing but a number to them with dollar signs attached. So, one continent at a time, we plan on changing this.

This may sound a little salesy, but we’ve signed up more than 1.5m customers without spending a single penny on marketing. It’s simple really: if you solve an everyday problem, you don’t need to spend a gazillion dollars on fancy marketing campaigns.

 

OUR CULTURE 👫

To put it bluntly - it’s about getting shit done and owning what you do. We don’t hide behind fancy job titles or set up bureaucratic processes. Instead we treat our people equally, fairly and give them a ton of freedom and autonomy to create something awesome.

We make mistakes, we learn from them and we back everything up with data and logic.

In two years, we’ve grown to over 350 people and we’re adding around 30 new additions each month. From engineers to marketers, we’re on the hunt for exceptional talent to help us scale our business and get Revolut in the hands of millions of people everywhere.

 

WHAT WE NEED 🚀

We are looking for a Data Scientist that will work on the anti-fraud system.

 

WHAT YOU’LL BE DOING

  • Building robust rule-based and machine learning models
  • Analysing and investigating fraud trends and attack vectors
  • Working closely with product owners, backend engineers and other data scientists on improving data infrastructure
  • Setting up experiments and evaluating results

 

WHAT SKILLS YOU’LL NEED 📖

  • Fluency in SQL and Python
  • Experience with big data technologies (BigQuery, Hadoop, Spark)
  • Experience deploying production applications with Docker/Kubernetes
  • Familiarity with messaging systems (Kafka, RabbitMQ, Cloud PubSub)
  • Good knowledge of at least 1 ML library: XGBoost, CatBoost, SKLearn
  • Deep understanding of statistics and ML algorithms
  • Fraud prevention experience preferred
IT & TechViktoria Popova