Senior Data Scientist

03 set - Milano
Klarna

Job-ID: 6a88bbba-1d3e- -f52a8218fd27Location: Stockholm; Milan; LondonSalary:
Si candidi ora: legga i dettagli del lavoro scorrendo verso il basso. Verifichi di possedere le competenze necessarie prima di inviare la candidatura.
- SEKType: Full timePosted: Contact: you will do Perform independent end-to-end validation of fraud detection ML models, including conceptual soundness, data integrity, feature engineering, model development, deployment design, and monitoring frameworks.
Develop challenger models.
Review and challenge first-line fraud model methodologies, assumptions, and implementation choices (e.g., scikit-learn, LightGBM, graph models, anomaly detection techniques, GenAI components).
Build and deploy agentic AI tools to support model validation workflows — automating review of model documentation and code, surfacing risks and inconsistencies.
Assess model performance using appropriate fraud metrics (e.g., precision/recall, ROC-AUC, PR-AUC, cost-sensitive metrics, fraud rate capture, business impact trade-offs).
Evaluate model stability, drift detection,



retraining strategies, and production monitoring practices.
Independently replicate model results where necessary and conduct challenger analyses to assess model robustness and limitations.
Review large-scale transaction datasets and feature pipelines (e.g., >100M transactions, hundreds of features) to assess data representativeness, leakage risks, and bias.
Evaluate model governance documentation, explainability approaches, and transparency — including regulatory compliance related to model risk, fairness, and data privacy.
Validate new technologies applied in fraud detection, such as Graph Networks, Behavioral Biometrics, Anomaly Detection, and GenAI-based systems.
Assess controls around CI/CD pipelines, deployment processes (e.g., Docker, Jenkins), and cloud environments (e.g., AWS SageMaker, S3, Athena, Lambda).
Develop and maintain validation frameworks, testing standards, and model performance monito

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