Senior Fraud Data Analyst

Klarna makes shopping smoooth. And we do it with flair because shopping is fun. Every day, we help customers, businesses, and partners explore just how smoooth the modern shopping experience can be.

It means we’re constantly changing the game. Always trying out new things. And we encourage our people to do the same. To grow. To develop. Because we don’t believe roles have to stay fixed. Instead we inspire our people to take an irregular career path. As a company of 350 dynamic start-ups, our whole business is built for it. So once you’re in, there’s no telling what will happen next.

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.

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. Our Analysts aim to identify these patterns with the help of manual and automated tools to protect our business, merchants and consumers from any fraud related losses and risks.

• • 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
  • Act as a trainer and consultant for our internal and external stakeholders.

Who you are

• • Klarna is looking for ambitious people with significant drive! 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 produce best work results! At Klarna we embrace change, you should dare to challenge the status quo and be persistent.
  • We have roles fit for either someone starting their career or ready to lead teams as a senior manager.

You should have

• • 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

You might also have

• • Experience​ ​of​ ​decision​ ​systems,​ ​including​ ​rule/strategy​ ​implementation​ ​and testing​ ​is​ ​preferred
  • Fraud experience – knowledge of external fraud data sources and use cases to prevent fraud
  • Preferably an understanding for how to perform data extraction and manipulation in multiple programming languages is a plus (MatLab, Java, C# etc…)

Send over a CV in English.