Senior Data Scientist

10 ore fa

Pavia, Lombardia, Italia Klarna Tempo pieno

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Overview In this second-line role, you validate fraud models used to protect payments, logins, and identity at Klarna. You’ll reproduce results, stress-test methodologies, and ensure governance and production readiness across the full model lifecycle. You work closely with first-line teams to surface risks and maintain model trust at scale. You’ll shape validation tooling and agentic AI workflows to keep validation pace with rapid development. This is a mission-driven opportunity to strengthen fraud defenses at a large, data-driven fintech. Retribuzione / Benefits
* competitive compensation
* hybrid/onsite work (2–3 days in office)
* diverse, inclusive culture
* opportunity to work with cutting-edge AI
* impactful role in safeguarding payments
* career growth and cross-team collaboration Responsabilità
* Assess model performance using fraud-specific metrics and balance business trade-offs
* Review large transaction datasets and feature pipelines for representativeness and leakage
* Evaluate drift detection, retraining strategies, and production monitoring
* Assess CI/CD and deployment controls (Docker, Jenkins, AWS) for model environments
* Evaluate governance documentation, explainability, and regulatory compliance
* Validate emerging techniques (graph networks, anomaly detection, GenAI-based systems) and document risks
* Communicate validation outcomes and risks to data scientists, ML engineers, and stakeholders Requisiti fondamentali
* 3+ years hands-on fraud modeling
* Fluency in Python and SQL; experience with PySpark or Spark
* Experience with tree-based models (LightGBM), anomaly detection, graph/network models
* Experience across ML lifecycle from feature engineering to deployment and monitoring
* Ability to explain complex models and communicate to non-technical stakeholders
* Knowledge of model risk governance, bias, fairness, and privacy considerations
* Experience building or validating agentic AI workflows
* Bonus: advanced degree in quantitative field; domain experience in BNPL or payment products
* Mentor or lead validation discussions is a plus
* strong communication skills
* ability to challenge approaches constructively
* detail-oriented with risk awareness
* LightGBM
* anomaly detection
* graph models

Senior Data Scientist

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