Fraud Analyst (various levels)

About Klarna

Klarna was founded in Stockholm, Sweden in 2005. Since then we've changed the banking industry forever. And now we're creating the world's smoothest shopping experience. We serve over 90 million consumers worldwide, and partner with 250,000 merchants – with a new merchant joining us every 8 minutes. Including some of the world's leading brands, such as H&M, ASOS, IKEA, Adidas, Samsung and Lufthansa. Our offices are spread over 17 different markets, hosted by 5000+ employees from 100+ nationalities.

Klarna strives to become the world’s favourite way to buy, and you can contribute to reaching this goal! We are looking to hire great people, who are passionate about using their talents to generate success. Analytics is no exception! We are currently looking to grow our Analytics teams to satisfy the company’s ever increasing need for complex problem solving and data driven decision making.

We are looking for ambitious people with significant drive! We need problem solvers, initiative takers, people that see opportunities and potential to improve. You should be passionate about your job and enjoy a fast paced international working environment. You will play an important role in taking Klarna to the next level - thus, you should desire to go above and beyond to deliver and grow as an individual. At Klarna we embrace change, you should dare to challenge the status quo and be persistent in doing so.

Analytics at Klarna is divided into several teams with their unique responsibilities. One of these teams is our Fraud Analytics Team, which focuses on the continuous improvement of our fraud real-time decisioning for every transaction processed by Klarna. E-Commerce is changing quickly and so do the patterns of fraud. We are looking for a number of analysts at varying levels to join our team! Our Analysts aim to identify these patterns with the help of various tools to protect our business, merchants and consumers from any fraud related losses and risks.

What you will do:

  • Use statistical analysis tools and techniques to develop automated fraud detection and real-time decisioning strategies
  • Collaborate with Data Scientists to build and implement fraud pattern models
  • Work with other teams across the business (particularly Engineering, Product and Commercial) to devise robust fraud strategies for new products and markets
  • Create, test and monitor new fraud tools and strategies from scratch
  • Work on proof of concepts involving new technologies and proactively seek out vendor and internal solutions to fraud problems
  • Ensure metrics and strategies are fit for purpose in terms of the current fraud environment and emerging threats
  • Work closely with the investigations team to understand threats and develop mitigations
  • Communicate and involve stakeholders to respond to any fraud related incidents as the first touchpoint for Legal, Finance, Engineering, Data Science and other partners

Who you are:

  • A degree from a university in a numerate subject (e.g. Economics, Science, Engineering, Mathematics)
  • Exceptional analytical thinking abilities, decision making and problem solving skills
  • Strong proficiency in SQL with the ability to analyse large quantities of data using statistical analysis tools such as Python or R
  • Experience in the entire Analytics lifecycle, from requirements gathering, data extraction, manipulation and analysis to sharing insights and advising on decision making
  • Excellent track record in optimizing business performance and identifying gaps in business strategy, with a focus on financial services, ideally fraud
  • Working proficiency and communication skills in verbal and written English
  • Fantastic stakeholder management skills
  • Passion for learning about Fraud
How to apply

Send over a CV in English.

Klarna is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates. Please refrain from including your picture and age with your application.