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Product Manager – Anti Fraud
Nebius Group. Own the end-to-end anti-fraud product roadmap covering signup/KYC checks, payment fraud detection, account takeover protection, and compute-abuse prevention .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in managing anti-fraud product roadmaps, including KYC checks and payment fraud detection, while leveraging strong analytical skills and collaboration with engineering and data science teams. Proficient in defining metrics and signals for fraud detection and ensuring compliance with legal and data privacy requirements.
Highest-signal resume keywords
Product Management Experience in FraudStrong Analytical SkillsSQL ProficiencyCollaboration with Engineering and Data ScienceUnderstanding of Payment Fraud and KYC/AML
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Product ManagementFraud DetectionRisk ScoringData AnalysisSQLKYC/AML ComplianceMetrics TrackingML-Based Detection SystemsIncident ManagementChargeback Analysis
Soft Skills
Decision Making Under AmbiguityCollaborationCommunication
Tools & Technologies
CloudSaaSFintechData Science ToolsAnalytics Platforms
Industry Keywords
Trust & SafetyPayment FraudChargebacksDevice/Network SignalsCompute Abuse
Tech Stack
Tools & technologiesCloudSQL
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 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
Benefits
Comp & perks- 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