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Lead the development of consumer credit risk models (PD, portfolio valuation) using ML and statistical methods, ensuring regulatory compliance and business impact in Klarna's BNPL operations.
Builds and deploys machine learning models to analyze open banking data for fraud prevention and credit risk decisions, working closely with engineering to operationalize insights at scale.
Builds and deploys machine learning models to turn bank transaction data into fraud and credit risk insights, working closely with engineering to operationalize models at scale.
What you will do We are rebuilding our fraud detection systems from the ground up, and we are looking for data scientists who want the full mandate to do it right, from raw data to production model, at a scale that…
Klarna, briefly At Klarna, we're building an everyday finance network, helping over 120 million consumers across 26 countries save time and money, and worry less about their finances. Working here means taking on…
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