Senior/Lead Data Scientist

PLP Group; London; On-site; NOK 700,000 - 900,000; Full time

Job summary

PLP Group is looking for a Lead Data Scientist to advance consumer-level credit scoring models in Norway, Innlandet. The successful candidate will have over 5 years of experience in credit risk modeling and be proficient in developing and validating Probability of Default models. Responsibilities include maintaining real-time models and ensuring regulatory compliance. If you have strong Python and SQL skills and are familiar with machine learning techniques, we invite you to apply. This role also involves mentoring junior members of the team and contributing to strategic credit policies.

Qualifications

• 5+ years’ experience in credit risk modeling for consumer lending, credit cards, or BNPL.
• Deep proficiency in PD model development and validation.
• Advanced Python and SQL skills.

Responsibilities

• Shape Klarna’s next-generation consumer-level credit scoring models.
• Design and maintain real-time PD models using statistical and ML approaches.
• Develop calibration frameworks and ensure compliance with regulatory standards.

Skills

Credit risk modeling

Probability of Default model development

Python

SQL

Machine Learning

Data explainability frameworks (SHAP, LIME)

Tools

XGBoost

scikit-learn

pandas

MLFlow

Job description

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.