Senior/Lead Data Scientist
Senior/Lead Data Scientist - Credit Risk Modeling 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.
- Develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies — including LLMs for explainability and feature engineering.
- Collaborate with cross-functional teams, translating modeling insights into strategic credit policies and business value.
- Mentor junior team members and contribute 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
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.
- Develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies — including LLMs for explainability and feature engineering.
- Collaborate with cross-functional teams, translating modeling insights into strategic credit policies and business value.
- Mentor junior team members and contribute 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