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 (Pavia)
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📍 Pavia