Senior/Lead Data Scientist (Credit Risk Modeling)

TL;DR

Senior/Lead Data Scientist (Credit Risk Modeling): Designing and maintaining real-time Probability of Default (PD) models and portfolio valuation for global consumer underwriting with an accent on statistical ML approaches and economic return optimization. Focus on developing calibration frameworks, ensuring regulatory compliance, and exploring LLMs for explainability and feature engineering.

Location: London, UK

Salary: £81,425 – £116,438

Company

Klarna is a leading global fintech company specializing in consumer credit and payment solutions.

What you will do

• Shape next-generation consumer-level credit scoring and portfolio valuation models.
• Design and maintain real-time PD models using statistical and ML approaches.
• Develop calibration frameworks and ensure compliance with regulatory and fairness standards.
• Explore novel methodologies, including LLMs for explainability and feature engineering.
• Translate modeling insights into strategic credit policies and business value.
• Mentor junior team members and contribute to the long-term modeling vision.

Requirements

• 5+ years of experience in credit risk modeling for consumer lending, credit cards, or BNPL.
• Deep proficiency in PD model development, validation, and calibration techniques.
• Advanced Python and SQL skills, including experience with XGBoost, scikit-learn, pandas, and MLFlow.
• Experience with explainability frameworks such as SHAP, LIME, and PDP.
• Ability to communicate technical concepts clearly and influence cross-functional decisions.
• CV must be submitted in English.

Nice to have

• Hands-on experience using LLMs to extract features from unstructured data.
• 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.