Senior/Lead Data Scientist -Credit Risk Modeling

Klarna; Milano; In loco; EUR 120.000 - 160.000; Tempo pieno

Descrizione del lavoro

Klarna is seeking a Lead Data Scientist for credit risk modeling to shape next-generation consumer-level scoring and portfolio valuation models. You will design real-time PD models, calibrate them, and integrate them into underwriting frameworks to optimize economic returns.

You will mentor junior team members, collaborate across functions, and stay aligned with regulatory and fairness standards while exploring novel ML approaches including LLMs for explainability.

Competenze

• 5+ years in credit risk modeling for consumer lending, credit cards, or BNPL.
• PD model development and validation with calibration techniques.
• Advanced Python and SQL skills with XGBoost, scikit-learn, pandas, MLFlow.
• Experience with explainability frameworks such as SHAP, LIME, PDP.

Mansioni

• Design, develop and maintain real-time PD models for underwriting and portfolio valuation.
• Create calibration frameworks and ensure regulatory and fairness compliance.
• Collaborate with cross-functional teams to translate modeling insights into policy and value, mentoring juniors.

Conoscenze

Python

SQL

XGBoost

scikit-learn

pandas

MLFlow

Explainability tools

Strumenti

SHAP

LIME

PDP

Descrizione del lavoro

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.