Senior Credit Risk Manager

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 200,000 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 3500+ employees from 90 nationalities.

We’re looking for an ambitious Senior Credit Risk Manager to lead our New York analytics team and help drive Klarna’s US point of sale credit strategy for our Pay in 4 and Financing products. This is a key role and will play a critical part in Klarna’s success. The role is an excellent fit for someone with an entrepreneurial attitude and a preference towards ownership, building, and action. 

What you'll do:

  • Define, build, and optimize the credit strategy for Klarna’s Pay Later, Pay in Four, and Financing products in the US 
  • Lead cross functional initiatives in model building, data acquisition, risk variable creation, and setting / prioritize the US credit risk team roadmap 
  • Be the accountable lead for a group of experienced analysts and be responsible for their performance and growth at Klarna
  • Be the bridge between US Credit Risk and Klarna HQ in Stockholm and Berlin by working in a highly cross functional environment with leaders from product management, data science, and engineering
  • Manage Klarna’s US loan book by participating in monthly risk committees, presenting to the senior leadership / CXO team, continuously reporting and analyzing book performance, and having ownership over loss curves

What we're looking for:

  • 5-10 years in credit risk strategy: preferably in consumer lending and with experience in financial technology. Experienced in PD modelling, line strategy setting, and building effective rules to separate risk.  
  • Experienced manager of high performance team: demonstrated experience of 2+ years leading a team of analysts
  • Experience in working with credit bureaus and data furnishers: obtaining variables, parsing data, performing retrospective analysis, building models
  • Strong quantitative skill set: expert ability in SQL, experience building models and  performing analysis in Python / R 
  • Best practice knowledge in credit risk: strong understanding of the full lifecycle from origination to debt collection -- participated in envisioning and building credit policies from scratch