What you will do As a Senior Data Scientist within our Open Banking team, you will build the analytical foundation that turns raw bank account data into reliable, actionable insight for fraud prevention and underwriting decisions. You will engage in feature engineering across incoming and outgoing cash flows to model affordability, and develop machine learning models that estimate probability of default and produce fraud scorecards. You will own the full lifecycle of these models, from raw data through to production deployment, working closely with engineering to operationalize your work at scale. You will also help monitor model performance, impact, and acceptance rates through dashboards you help build, and you will partner closely with the Credit Modeling and Fraud teams to align on shared goals and infrastructure. Who you are Experience building and deploying machine learning models end to end, from raw data to production Strong feature engineering skills, ideally with transactional or financial data Proficient in Python and SQL, with experience working in AWS environments Solid understanding of classification modeling techniques for risk or fraud use cases Comfortable partnering closely with engineering teams to bring models into production Strong communication skills, with the ability to work cross-functionally with Credit Modeling and Fraud teams A curious, ownership-driven mindset, comfortable building infrastructure and processes from scratch Awesome to have Experience with open banking data or affordability modeling Familiarity with building dashboards for model monitoring, ideally with tools like Databricks Experience with monitoring and observability tools such as Datadog Background in underwriting, credit risk, or fraud detection use cases Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site!