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Klarna

Senior/Lead Data Scientist -Credit Risk Modeling

Klarna London, England, United Kingdom · £81K–£116K/yr

Software Development · 1,001-5,000 employees

Jul 23
data-scientist Senior (5-10 yrs) Full-time United Kingdom
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About the role

You will design and maintain real-time probability of default models to optimize underwriting and economic returns. Additionally, you will collaborate with cross-functional teams to translate modeling insights into strategic credit policies while mentoring junior team members.

What they look for

Credit Risk Modeling PD Modeling Python SQL XGBoost Scikit-learn Pandas MLFlow SHAP LIME PDP LLMs Feature Engineering Statistical Modeling Machine Learning Calibration

Requirements

Candidates must have 5+ years of experience in credit risk modeling for consumer lending or similar financial sectors. Proficiency in Python, SQL, and advanced machine learning frameworks is required, along with strong communication skills.

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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