Product Manager – Anti Fraud

• Own the end-to-end anti-fraud product roadmap covering signup/KYC checks, payment fraud detection, account takeover protection, and compute-abuse prevention
• Own rules and risk-scoring tooling for analysts and data scientists to define, test, and deploy detection rules and ML models with guardrails and audit trails
• Own manual review and case-management experiences for Trust & Safety operations, including queues, evidence views, and action workflows
• Own customer-facing verification flows, step-up challenges, and appeals while minimizing false positives
• Define signals, alerts, and thresholds to identify fraud and abuse incidents early
• Participate in incident reviews and post-mortems, converting root causes into improvements to detection rules, models, and roadmap
• Drive triage, ownership, and mitigation of active incidents with Trust & Safety, Engineering, and Data Science
• Write PRDs and specifications translating risk problems into engineering and data-science work
• Partner with Analytics on detection models, defining problems, labels, success criteria, and rules-versus-ML decisions
• Run experiments and monitor rollouts, tracking fraud-catch metrics and customer-friction impact
• Work with Legal/Compliance on payment-network rules, KYC/AML expectations, and data-privacy requirements
• Track and report fraud loss, chargeback rate, false-positive rate, review throughput, and time-to-detection

• Proven product management experience in fraud, risk, trust & safety, or payments
• Strong analytical skills; comfortable with data, SQL or equivalent, and reasoning about precision/recall trade-offs and metrics
• Ability to make decisions under ambiguity and balance security, business, and customer-experience priorities
• Solid collaboration with engineering and data science; ability to hold a technical conversation about signals, features, and model behavior
• Exposure to cloud, SaaS, marketplace, fintech, or infrastructure products
• Understanding of payment fraud, chargebacks, KYC/AML, or device/network signals (fingerprinting, velocity, IP reputation)
• Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility as a condition of hire
• Familiarity with ML-based detection systems and their operational lifecycle (drift, retraining, monitoring) — added bonus
• Experience with abuse patterns specific to compute or GPU platforms (mining, credential stuffing, free-tier farming) — added bonus

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment and talented teams