ApplyCV

Jobs › Data, ML & AI › Klarna

Senior/Lead Data Scientist -Credit Risk Modeling

Klarna · London · Full time · Posted 3 months ago

Hiring from abroad

The job description doesn't mention visas, relocation or other languages. Most don't, so it's worth asking before you apply. See jobs that do mention help.

What data and ML jobs in the United Kingdom say about visas →

Read from the job description's own text. Check the original before relying on it.

At Klarna, our credit risk models sit at the heart of how we underwrite and price risk for millions of consumers globally. We're looking for a Lead Data Scientist to help shape the next generation of consumer-level credit scoring and portfolio valuation models. What you'll do As a Lead Data Scientist within credit risk modeling, you will shape Klarna's next-generation consumer-level credit scoring and portfolio valuation models. You'll design and maintain real-time PD (Probability of Default) models using statistical and ML approaches, integrating them into frameworks for underwriting and economic return optimization. You'll develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies — including LLMs for explainability and feature engineering. Collaborating with cross-functional teams, you'll translate modeling insights into strategic credit policies and business value, while mentoring junior team members and contributing to Klarna's long-term modeling vision. Who you are 5+ years' experience in credit risk modeling for consumer lending, credit cards, or BNPL. Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques. Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow. Experience with explainability frameworks such as SHAP, LIME, PDP. Ability to communicate technical concepts clearly and influence cross-functional decisions. Familiarity with real-time modeling and current trends in ML and credit analytics. Awesome to have Hands-on experience using LLMs to extract features from unstructured data (e.g., customer communications, credit applications). Knowledge of integrating third-party credit bureau data into production models. Understanding of champion/challenger model frameworks and A/B testing infrastructure. Exposure to loan-level economic modeling, including cost-of-capital and loss metrics. Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site!

The Apply button goes to the company's own form. ApplyCV does not sit in between and does not see your application. Text above is the employer's; check the original before relying on it.