Overview
You will perform end-to-end validation of fraud detection ML models, covering data, features, models, deployment, and monitoring. You’ll develop challenger approaches and scrutinize methodologies used by first-line teams. You will build agentic AI tools to automate validation workflows and surface risks. Your work directly supports governance, regulatory expectations, and responsible deployment in a fast-paced payments environment.
Responsabilità
- Validate end-to-end fraud ML models, including data integrity, features, deployment design, and monitoring
- Develop challenger models and critique first-line methodologies and implementations
- Build and deploy agentic AI tools to automate validation workflows and surface risks
- Assess model performance using fraud-specific metrics and business impact trade-offs
- Evaluate data representativeness, leakage risks, bias, and large-scale feature pipelines
- Review model governance, explainability, privacy, and regulatory compliance
- Assess CI/CD controls, deployment processes, and cloud environments
- Develop and maintain validation frameworks and monitoring tools
- Collaborate with data scientists, ML engineers, product, and business stakeholders
- Document validation outcomes in line with governance standards and regulations
- Stay updated on fraud typologies, ML/AI techniques, and regulatory developments
Requisiti fondamentali
- Advanced degree in a quantitative field (Master’s or PhD)
- 3+ years of hands-on fraud modeling experience
- Strong ML methods for fraud detection (tree-based models, anomaly detection, graph models)
- Deep ML lifecycle expertise from design to production monitoring
- Strong Python and SQL; PySpark/Spark
- Experience with agentic AI workflows
- Familiarity with cloud ML platforms (AWS SageMaker, Lambda, S3, Athena) and deployment
- Knowledge of model validation, governance, and regulatory expectations
- Experience assessing bias, fairness, and privacy risks
- Strong communication and ability to explain risks to senior stakeholders
- Ability to work independently while constructively challenging teams
- analytical thinking
- clear communication
- collaborative mindset
- Python
- SQL
- PySpark
Senior Data Scientist - Fraud Model Validation datore di lavoro: Klarna
Klarna è un datore di lavoro eccezionale, offrendo un ambiente stimolante dove gli ingegneri possono affrontare sfide uniche e significative nel settore finanziario. Con una cultura del lavoro collaborativa e flessibile, i dipendenti hanno l'opportunità di crescere professionalmente, contribuendo a progetti innovativi che utilizzano l'IA. Inoltre, la posizione in un contesto internazionale permette di lavorare con team diversificati, arricchendo ulteriormente l'esperienza lavorativa.
