Principal Product Manager, Fraud & Risk Platform

Expedia Expedia · Hospitality · Seattle, WA

Principal Product Manager for Expedia's Fraud & Risk Platform, focusing on defining strategy, driving roadmaps, and partnering with engineering/data science to advance AI/ML-driven fraud detection and risk-scoring systems. The role balances fraud loss reduction with customer friction and protects the business while enabling growth.

What you'd actually do

  1. Define and evolve the long-term product strategy and vision for fraud prevention and risk management capabilities across a complex, global travel ecosystem, ensuring alignment with organizational objectives.
  2. Drive an integrated roadmap for a suite of fraud and risk products that balances fraud loss reduction, customer friction, conversion, and operational cost, securing buy-in from cross-functional partners.
  3. Partner closely with engineering and data science leaders to advance the technical foundation of fraud detection and risk-scoring systems, including AI/ML-driven anomaly detection, behavioral analytics, and pattern recognition.
  4. Own key fraud and risk performance metrics such as fraud loss rate, false-positive rate, chargeback ratio, and approval/friction rates, making data-driven decisions on build-vs-buy, vendor tooling, and lifecycle evolution of capabilities.
  5. Identify emerging fraud and risk threats, connect the right stakeholders, and lead complex, cross-functional initiatives and escalations across security, compliance, legal, engineering, and customer experience to rapidly mitigate risk.

Skills

Required

  • Product leadership roles focused on fraud, payments, risk
  • Ownership of end-to-end performance for fraud and risk products or platforms
  • Accountability for metrics such as fraud loss, false positives, chargebacks, and customer friction
  • Expertise in AI/ML application to fraud detection, including anomaly detection, behavioral analytics, and pattern recognition
  • Familiarity with AI-driven systems, tools, or workflows
  • Applying AI/ML concepts to real world products
  • Strong fluency in data science principles
  • Statistical reasoning
  • Agile practices
  • Translate complex technical and threat landscape considerations into clear product requirements

Nice to have

  • Deep domain knowledge spanning fraud, payments, chargebacks, dispute management, and AML/KYC fundamentals
  • Shaping organization-level fraud and risk strategy in ambiguous, high-stakes environments
  • Partnering with engineering and data science teams to architect and evolve AI/ML-enabled fraud detection and risk-scoring systems at scale
  • Establishing responsible AI practices for model evaluation, monitoring, tuning, retraining, and bias mitigation
  • Reverse engineer fraud patterns and adversarial behaviors
  • Monitor emerging AI/ML and fraud trends (such as graph-based detection, behavioral biometrics, or generative-AI-enabled fraud)
  • Translate these into innovative, scalable product capabilities
  • Influencing senior stakeholders beyond the immediate product area
  • Resolving cross-workstream escalations
  • Coaching product managers on integrating fraud and risk considerations into customer journeys, communications, and decision-making
  • Safely integrates and operates AI/ML‑enabled solutions that improve outcomes
  • Advanced experience applying AI/ML to large-scale fraud and risk environments to reduce loss while enhancing legitimate customer experience and driving sustainable business growth

What the JD emphasized

  • AI/ML application to fraud detection
  • AI/ML-enabled solutions
  • responsible AI practices for model evaluation, monitoring, tuning, retraining, and bias mitigation
  • emerging AI/ML and fraud trends

Other signals

  • AI/ML detection capabilities
  • AI/ML-driven anomaly detection
  • AI/ML insights to optimize fraud and risk models
  • AI/ML-enabled solutions