Senior/Lead Data Scientist -Credit Risk Modeling

Overview

As Lead Data Scientist in Klarna’s credit risk team, you will shape next‑generation consumer credit scoring and portfolio valuation models. You will design real‑time PD models and calibration frameworks that support underwriting and economic return optimization, while ensuring regulatory and fairness standards. You’ll explore advanced methods, including LLMs for explainability, and mentor junior colleagues, contributing to Klarna’s long‑term modeling vision. This role offers impact across cross‑functional teams and a chance to influence credit policy at scale.

Responsibilities

• Shape and maintain next‑generation consumer credit scoring and portfolio valuation models
• Design and operate real‑time PD models used in underwriting and risk optimization
• Develop calibration frameworks and ensure regulatory and fairness standards
• Explore novel methodologies including LLMs for explainability and feature engineering
• Collaborate with cross‑functional teams to translate insights into policy and business value
• Mentor junior team members and contribute to the long‑term modeling roadmap

Key requirements

• 5+ years’ experience in credit risk modeling for consumer lending, credit cards, or BNPL
• Deep proficiency in PD model development and validation; calibration techniques
• Advanced Python and SQL skills; familiarity with XGBoost, scikit-learn, pandas, MLFlow
• Experience with explainability frameworks such as SHAP, LIME, PDP
• Clear communication and ability to influence cross‑functional decisions
• Familiarity with real‑time modeling and current trends in ML and credit analytics

• strong communication
• cross‑functional collaboration
• mentoring and leadership
• PD model development and validation
• calibration techniques
• Python

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