Principal Product Manager, Fraud & Risk Platform

Expedia•Seattle, WA

About The Position

Expedia Group is seeking a highly influential individual contributor to architect the long-term strategy for its fraud prevention and risk management products across its diverse, global travel ecosystem. This role will spearhead complex, cross-functional initiatives that integrate advanced AI/ML detection capabilities, balance fraud loss reduction against customer friction, and protect the business while enabling growth. This leadership role demands strategic acumen, deep technical fluency, and a collaborative spirit to safeguard travel experiences globally.

Requirements

12+ years of relevant experience with a Bachelor’s degree, or 10+ years with a Master’s degree, in product leadership roles focused on fraud, payments, risk, or closely related domains or equivalent practical experience.
Proven ownership of end-to-end performance for fraud and risk products or platforms, including accountability for metrics such as fraud loss, false positives, chargebacks, and customer friction across multiple workstreams or a suite of products.
Demonstrated expertise in AI/ML application to fraud detection, including anomaly detection, behavioral analytics, and pattern recognition, with familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products.
Strong fluency in data science principles, statistical reasoning, and agile practices, with the ability to translate complex technical and threat landscape considerations into clear product requirements for diverse, global stakeholders.

Nice To Haves

Deep domain knowledge spanning fraud, payments, chargebacks, dispute management, and AML/KYC fundamentals, with a track record of shaping organization-level fraud and risk strategy in ambiguous, high-stakes environments.
Extensive experience partnering with engineering and data science teams to architect and evolve AI/ML-enabled fraud detection and risk-scoring systems at scale, including establishing responsible AI practices for model evaluation, monitoring, tuning, retraining, and bias mitigation.
Proven ability to 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), and translate these into innovative, scalable product capabilities.
Demonstrated success influencing senior stakeholders beyond the immediate product area, resolving cross-workstream escalations, and 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, with 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.

Responsibilities

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.
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.
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.
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.
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.
Apply deep data analytics and machine learning insights to continuously optimize fraud and risk models, safely integrate and operate AI/ ML ‑ enabled solutions that improve outcomes, and foster a culture of coaching, knowledge-sharing, and inclusive collaboration across product teams.