Product Manager – Anti Fraud

This is a fully remote position, open to applicants in Netherlands.

📋 Description

• Take full responsibility for the comprehensive anti-fraud product roadmap, which includes signup/KYC checks, payment fraud detection, account takeover protection, and prevention of compute abuse.

• Manage rules and risk-scoring tools that allow analysts and data scientists to define, test, and implement detection rules and machine learning models, ensuring there are guardrails and audit trails.

• Oversee the manual review and case management processes for Trust & Safety operations, including managing queues, evidence views, and action workflows.

• Handle customer-facing verification processes, step-up challenges, and appeals, all while aiming to reduce false positives.

• Establish signals, alerts, and thresholds to detect fraud and abuse incidents at an early stage.

• Engage in incident reviews and post-mortem analyses, transforming root causes into enhancements for detection rules, models, and the overall roadmap.

• Lead the triage, ownership, and mitigation of ongoing incidents in collaboration with Trust & Safety, Engineering, and Data Science teams.

• Draft PRDs and specifications that translate risk challenges into actionable engineering and data science tasks.

• Collaborate with Analytics on detection models, identifying problems, labels, success criteria, and distinguishing between rules and machine learning decisions.

• Conduct experiments and monitor rollouts, keeping track of fraud detection metrics and the impact on customer experience.

• Work alongside Legal/Compliance teams to ensure adherence to payment network rules, KYC/AML regulations, and data privacy requirements.

• Monitor and report on fraud loss, chargeback rates, false-positive rates, review throughput, and time-to-detection.

⛳️ Requirements

• Demonstrated experience in product management within fraud, risk, trust & safety, or payment sectors.

• Exceptional analytical abilities; comfortable working with data, SQL or similar, and evaluating precision/recall trade-offs and metrics.

• Capable of making decisions in uncertain situations while balancing security, business needs, and customer experience priorities.

• Strong collaboration skills with engineering and data science teams; able to engage in technical discussions regarding signals, features, and model behaviors.

• Familiarity with cloud, SaaS, marketplace, fintech, or infrastructure products.

• Knowledge of payment fraud, chargebacks, KYC/AML, or device/network signals (such as fingerprinting, velocity, and IP reputation).

• Candidates must be authorized to work in the country where they apply and provide proof of employment eligibility as a condition of hire.

• Understanding of ML-based detection systems and their operational lifecycle (including drift, retraining, and monitoring) is a plus.

• Experience with abuse patterns related to compute or GPU platforms (such as mining, credential stuffing, and free-tier farming) is an additional advantage.

🏝️ Benefits

• Competitive compensation.

• Opportunities for career growth and learning.

• Flexibility and a sense of ownership.

• A collaborative and innovative organizational culture.

• Chance to contribute to significant AI projects.

• An international work environment with talented teams.