Senior Product Manager - Fraud & Risk

Senior Product Manager, Fraud & Risk Platform  

Introduction to the Team:   

The Product Team creates high-quality end-to-end experiences for travelers, partners, and Expedia Group. Our focus on customer-centric innovation enables us to develop products that build loyalty and repeat business. We partner closely with teams across Expedia Group to drive growth and achieve results for our customers and the company.  

As a Senior Product Manager on the Fraud team, you will own the strategy and delivery of the products that protect Expedia Group and its travelers from fraud, abuse, and financial crime. This is a role defined by hard tradeoffs.  Every dollar loss prevented risks adding friction for a legitimate customer, and your job is to find the sharpest possible edge between the two. You'll set the vision for your sub-domain, build a roadmap the business can defend, and lead the AI/ML detection capabilities that let it scale against adversaries who adapt faster than most products ever face. You'll do it by investing in championing your product and the market, evolving into an SME earning the trust of engineering, Ops and data science, influencing business leaders and partners who don't report to you, and coaching the PMs coming up behind you. 

In This Role You Will:  

• Define and drive the product vision and strategy for holistic fraud prevention and risk management capabilities across Expedia Group’s ecosystem, clearly articulating loss‑versus‑friction trade‑offs to senior stakeholders in growth, finance, operations, and legal. 

• Build and own an integrated, data‑driven roadmap for assigned fraud and risk products where each milestone is tied to measurable impact on fraud loss rate, insult rate, trust damage, chargebacks, approval/failure rates, and review‑queue cost, and defend prioritization in the face of competing business objectives informed by global market dynamics. 

• Lead collaboration with engineering, data science, and analytics to build or buy real‑time, low‑latency fraud detection and risk‑scoring systems, including AI/ML‑driven anomaly detection, graph and entity‑linking, behavioral analytics, and pattern recognition while managing rule complexity and technical debt. 

• Operate effectively in ambiguous, adversarial environments by independently modeling dollars at stake, applying investigative techniques such as attack‑vector discovery, adversarial red‑teaming, and fraud‑ring analysis, and translating insights into scalable, production‑ready product capabilities. 

• Partner across payments, supply, identity, trust & safety, risk operations, UX, compliance, and legal to design secure, traveler‑centric  user flows, and to ensure that fraud‑risk considerations are embedded across end‑to‑end user journeys and decisioning workflows. 

• Define, monitor, and communicate key fraud and risk KPIs, run rigorous experimentation (including champion/challenger tests and holdouts), and translate detection performance and AI/ML model insights into clear narratives and recommendations that drive organizational alignment and product decisions. 

Minimum Qualifications: 

• Bachelor’s degree in a relevant field, or equivalent related professional experience. 

• 8+ years of relevant professional experience with a Bachelor’s degree, or 6+ years with a Master’s degree, in product management roles focused on fraud, risk, trust & safety, seller fraud, or payments, or in closely related domains. 

• Proven end‑to‑end ownership of fraud and risk products or platforms, including accountability for metrics such as fraud loss, false positives/insults, chargebacks, customer friction, and operational review‑queue cost for a significant product area or set of related capabilities. 

• Demonstrated experience collaborating with engineering and data science teams to design, launch, and iterate on fraud detection and risk‑scoring solutions, including real‑time decisioning services, with strong fluency in data‑driven decision making, data science principles, statistical reasoning, and agile delivery practices. 

• Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products. 

Preferred Qualifications: 

• Deep domain expertise across fraud, payments, supplier fraud, chargebacks, dispute management, and AML/KYC fundamentals, with a track record of shaping product‑level or domain‑level fraud and risk direction informed by deep competitive insightsand independently modeling financial impact to inform strategy and prioritization. 

• Significant experience partnering with engineering and data science to design and enhance AI/ML‑enabled fraud detection and risk‑scoring capabilities (including anomaly detection, graph‑based methods, and behavioral analytics), and safely integrates and operates AI/ML‑enabled solutions that improve outcomes in large‑scale production environments. 

• Demonstrated ability to analyze and reverse‑engineer fraud patterns and adversarial behaviors, employing investigative approaches such as attack‑vector discovery, fraud‑ring analysis, and adversarial red‑teaming, and translating these insights into robust product features, decision flows, and controls. 

• Proven effectiveness influencing and aligning senior leaders across growth, finance, operations, legal, and compliance, resolving cross‑team fraud and risk escalations, and enabling other product managers to incorporate fraud‑risk considerations into their roadmaps, customer journeys, and communication strategies. 

• Demonstrated experience taking products from concept to scaled adoption, informed by deep market research including defining success metrics, running experiments such as champion/challenger tests and holdouts, monitoring ongoing performance (loss, friction, and cost), and continuously optimizing along the loss‑versus‑friction curve using AI/ML and advanced analytics.