Analytics Manager - Fraud

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.

We are looking for someone to be part of the Fraud Strategy team for the APAC region. The team consists of analysts and data scientists across Europe & Australia. The Fraud strategy team belongs to the Fraud Prevention Group, 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.

As the Fraud analytics lead for Australia & New Zealand markets in collaboration with the Team Lead, you will define, measure, and own Fraud prevention KPIs at a portfolio, product, and merchant level.

What you'll do:

  • Manage the day to day operations of the fraud strategy for the region, ensuring that it is following best practices.
  • Ensure the team has visibility of policy/product performance.
  • Help the team to better scope their work by breaking down large deliverables into step wise value deliveries that do not require “big bang” implementations, but rather are driving continuous improvement, including quick validation of hypothesis.
  • Collaborate closely with the all stakeholders of the team, and be the “go-to” for those stakeholders.
  • Ensure that commercial and product considerations are baked in to our decisioning logic, and ensure that fraud decisioning logic is considered in new product launches.
  • Collaborate closely with the Fraud Prevention leaders/stakeholders within the Fraud Prevention Group to ensure that we have the optimal ways of working and effectiveness as a group.

You'll have:

  • 7+ years of relevant analytics experience.
  • Proficiency in SQL with the ability to analyse large quantities of data using statistical analysis tools such as Python or R.
  • An excellent track record in optimising business performance and identifying gaps in business strategy, with a focus on financial services, ideally within fraud.
  • An understanding of how the team affects the customer journey as well as the Klarna P&L.
  • Fantastic stakeholder management skills.
  • Understanding of the entire Analytics lifecycle, from requirements gathering, data extraction, manipulation and analysis to sharing insights and advising on decision making.
  • A passion for learning about Fraud!

You might also have:

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

Why Klarna

  • 5 weeks annual leave
  • Top tier health insurance with all the extras for you and any dependants/defacto you may have!
  • Life and income protection insurance
  • $500 annual health and wellness allowance
  • Annual home office allowance
  • Lunch is on us twice a week!
  • Weekly and monthly office celebrations
  • Secondments - AKA The chance to work in one of our global offices
  • Personal and professional development and training
  • Flexible working arrangements - work from anywhere 3 days a week!
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.