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Staff Product Manager - Fraud

Owns vision, strategy, and execution for Plaid's Identity Verification (IDV) and AML Monitor products within the fraud platform. Drives fraud prevention, compliance, and customer experience improvements through cross-functional collaboration. Requires 6+ years PM experience in fraud/risk/security.

207k – 306kCaliforniaProduct ManagementRemote6+ YOE

About the role

Responsibilities

  • Set the direction. Own the vision, strategy, and roadmap for IDV and Monitor end to end. Drive meaningful outcomes for fraud prevention, compliance, and customer experience.
  • Build the backbone. Grow IDV and Monitor as the core of Protect and Layer by expanding data coverage, improving decision quality, and enhancing reliability, latency, and transparency across systems.
  • Execute with focus. Partner closely with engineering, design, and other Fraud teams to move from concept to production with clear launch criteria and consistent follow-through.
  • Communicate with precision. Create clarity across teams by articulating decisions, tradeoffs and rationale crisply, translating complex systems into simple narratives and keeping partners aligned on what matters.
  • Stay close to the field. Engage with customers and GTM teams to spot fraud and compliance patterns early, translate them into product improvements, and maintain momentum through demos, integrations, and launches.

Qualifications

  • 6+ years of product management experience in fraud, risk, security, or identity.
  • Strong technical foundation with a degree in Computer Science or a related field preferred.
  • Experience building or integrating fraud detection, risk scoring, or IDV/AML systems.
  • Ability to write clear product requirements and communicate technical concepts to diverse audiences.
  • Comfortable working closely with engineering, data, and go-to-market teams to deliver measurable impact.

Nice to Have

  • Experience with data science or ML-driven systems, including model inputs and outputs.
  • Entrepreneurial or founder experience with a bias toward ownership and experimentation.

Skills

Fraud DetectionRisk ScoringIdvAMLKycProduct RequirementsMachine LearningData ScienceIdentity VerificationTransaction Monitoring

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