Machine Learning Scientist

Role overview Develop machine learning capabilities that help detect fraud and make risk decisions more accurate and understandable. The work spans analysis of large datasets, model design and evaluation, and close partnership with product, fraud specialists, and data engineering to bring useful approaches into production.

Responsibilities - Design and evaluate fraud detection models, including scoring approaches that combine multiple evidence sources. - Explore large datasets to find behavioral patterns, relationships, anomalies, and signals that can improve detection. - Define rigorous experiments and evaluation methods, including calibration, decision thresholds, and production-relevant performance measures. - Build interpretable approaches that help stakeholders understand model scores and decisions. - Investigate human-in-the-loop and causal methods for fraud decisioning. - Work with product, domain experts, and data engineering to operationalize models and improve them using production feedback. - Contribute to monitoring, governance, documentation, shared tooling, and team practices.

Requirements - Degree in computer science, statistics, mathematics, machine learning, or a related quantitative discipline, or equivalent practical experience. - Strong machine learning fundamentals and hands-on experience developing and evaluating models. - Ability to analyze complex, large-scale data and translate findings into practical detection improvements. - Experience designing robust experiments and assessing model performance in realistic conditions. - Ability to communicate model behavior and collaborate with product and technical partners.

Benefits and work setup The role offers remote or office-based work with flexibility. Listed compensation is €50,000–€70,000 base, plus a 10% annual bonus and equity. Benefits may vary by location and include healthcare options, retirement contributions, stock plan participation, paid leave, learning support, a home-office allowance, and optional coverage such as pet insurance.