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Klarna

Senior/Lead Data Scientist

Klarna Stockholm, Sweden · SEK 753K–SEK 1M/yr

Software Development · 1,001-5,000 employees

3 h ago
data-scientist Senior (5-10 yrs) Full-time Sweden
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About the role

Design and maintain real-time consumer credit scoring and portfolio valuation models, including probability-of-default models, calibration frameworks, and methods that support underwriting and economic return optimization. Ensure models meet regulatory and fairness standards, translate modeling insights into credit policies, explore new approaches such as LLMs, and mentor junior team members.

What they look for

Credit Risk Modeling Probability of Default Modeling Model Development and Validation Model Calibration Python SQL XGBoost Scikit-Learn Pandas MLflow SHAP LIME Partial Dependence Plots Real-Time Modeling Explainability Cross-Functional Communication

Requirements

Requires at least five years of consumer lending, credit card, or BNPL credit risk modeling experience, with deep expertise in probability-of-default model development, validation, and calibration. Candidates should have advanced Python and SQL skills, familiarity with the listed machine learning and explainability tools, and the ability to communicate technical concepts and influence cross-functional decisions.

Full description

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!

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