Senior data scientist - fraud model validation

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7ew2vv

Job-ID: 6a88bbba-1d3e-4389-9444- 100 M 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 Gen AI-based systems.

Assess controls around CI/CD pipelines, deployment processes (e.g., Docker, Jenkins), and cloud environments (e.g., AWS Sage Maker, S3, Athena, Lambda). Develop and maintain validation frameworks, testing standards, and model performance monitoring tools (e.g., SQL, Py Spark, Python-based validation libraries). Collaborate closely with first-line fraud data scientists, ML engineers, product, and business stakeholders to ensure transparent communication of model risks and validation findings.

Provide actionable recommendations and formally document validation outcomes in line with internal model governance standards and external regulatory expectations. Stay up to date with evolving fraud typologies, emerging ML/AI techniques, and regulatory developments in model risk management.

Who you are Advanced degree (Master's or Ph D) in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Physics, or Engineering. 3+ years of hands-on experience in fraud-related modeling (e.g., transaction fraud, account takeover, identity fraud, payments fraud etc). Strong expertise in machine learning methods used in fraud detection, including tree-based models (e.g.,



Light GBM), anomaly detection, graph/network models, and advanced ML techniques. Deep understanding of the end-to-end ML lifecycle — from conceptual design and feature engineering to production deployment and monitoring — with the ability to critically challenge each stage.

Strong programming skills in Python and SQL;

experience with Py Spark/Spark and large-scale data processing.

Experience building agentic AI workflows. Familiarity with cloud-based ML platforms (e.g., AWS Sage Maker, Lambda, S3, Athena) and production deployment workflows. Strong knowledge of model validation principles, model risk governance frameworks, and regulatory expectations.

Experience assessing model bias, fairness, explainability, and privacy risks. Excellent analytical thinking and structured problem-solving skills, with the ability to assess complex models and clearly articulate risks and limitations. Strong communication skills, capable of translating technical findings into clear, actionable insights for senior stakeholders and non-technical audiences.

Ability to work independently while constructively challenging first-line teams in a collaborative manner. Awesome to have Experience in BNPL, credit cards, payments, or other transaction-heavy financial products.

Experience validating models in highly regulated environments.

Experience mentoring junior validators or leading validation reviews. Exposure to inference of rejected transactions and understanding of fraud/credit overlap. Familiarity with AI governance frameworks and emerging AI regulatory requirements.

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7ew2vv