Lead Data Scientist, Credit Risk & Scoring

Deel; Greater London; Ibrido; GBP 90.000 - 140.000; Tempo pieno

Descrizione del lavoro

Klarna is seeking a Lead Data Scientist to shape next-generation consumer-level credit scoring and portfolio valuation models. You will design and maintain real-time PD models, calibrate frameworks, and ensure regulatory fairness while exploring LLM-based feature engineering.

You will collaborate with cross-functional teams, mentor juniors, and contribute to long-term modeling vision, leveraging Python, SQL, XGBoost, and MLFlow in a fast-paced environment.

Competenze

• 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.

Mansioni

• Shape Klarna’s next-generation consumer-level credit scoring and portfolio valuation models.
• Design and maintain real-time PD models and integrate into underwriting frameworks.
• Develop calibration frameworks and ensure regulatory fairness standards.
• Explore novel methodologies including LLMs for explainability and feature engineering.
• Collaborate with cross-functional teams and mentor junior staff.
• Contribute to Klarna’s long-term modeling vision.

Conoscenze

PD modeling

Model validation

Python

SQL

XGBoost

scikit-learn

pandas

MLFlow

Explainability

Communication

Real-time modeling

LLMs feature extraction

Credit risk

Strumenti

MLFlow

SHAP

LIME

PDP

XGBoost

scikit-learn

pandas

Python

SQL

Descrizione del lavoro

Klarna is seeking a Lead Data Scientist to shape next-generation consumer-level credit scoring and portfolio valuation models. You will design and maintain real-time PD models, calibrate frameworks, and ensure regulatory fairness while exploring LLM-based feature engineering.

You will collaborate with cross-functional teams, mentor juniors, and contribute to long-term modeling vision, leveraging Python, SQL, XGBoost, and MLFlow in a fast-paced environment.