Product Manager II - Digital Fraud

Job Summary

Required Qualifications

• •Digital Fraud product roadmap definition and maintenance
• •Discovery and solutioning for fraud capabilities including pre-authorization fraud checks, post-order decisioning, device fingerprinting, reject/recycle, chargeback automation, fraud data foundations, and fraud lifecycle improvements
• •Translation of business needs from Digital Loss Prevention, Payments, eCommerce, Mobile App, Treasury, Sales Audit, Store Ops, and Loyalty into clear product outcomes, user stories, acceptance criteria, and delivery plans
• •KPI definition and measurement for the product domain including fraud loss, cancel and chargeback trends, accept/reject/manual-review performance, demand-to-fulfillment impact, SLA/SLO considerations, false positives, operational friction, and customer experience impacts
• •Collaboration with vendors and internal platform teams to evaluate, pilot, implement, and continuously optimize fraud and risk capabilities while managing dependencies, contracts, and delivery risks
• •Design and evaluation of controlled experiments, A/B tests, and phased rollouts to measure fraud performance, conversion impacts, and operational outcomes
• •Upstream engagement to include Digital Fraud early in planning for new experiences, payment methods, loyalty programs, fulfillment changes, and AI/agentic commerce opportunities
• •Evaluation and support of machine learning, behavioral analytics, and AI-driven fraud detection capabilities while balancing explainability, governance, and customer experience
• •Monitoring of fraud, retail, digital commerce, and payment trends to proactively identify emerging risk patterns and shape product strategy
• •Monitoring of emerging fraud vectors including account takeover, promotion abuse, synthetic identities, bot attacks, and credential stuffing
• •Participation in fraud-related incident response, major issue management, and post-incident reviews
• •Drive of corrective actions following production incidents, fraud spikes, chargeback events, or vendor service disruptions
• •Comfort learning how fraud data, order events, risk signals, payment flows, and operational workflows connect across a complex retail ecosystem
• •Understanding of fraud decisioning & review systems including Riskified, Accertify, Signifyd, manual review workflows, fraud rules, risk thresholds, whitelists, and Digital LP review processes
• •Understanding of device, identity, and signal enrichment capabilities including device fingerprinting, Accertify JavaScript library, Athlete Record/scorecard data, Auth0 data opportunities, Akamai Edge Security, and risk velocity rules
• •Understanding of payments and chargebacks systems including Adyen, PayPal, Affirm, AfterPay, ApplePay, payment authorization adjacency, chargeback evidence, dispute defense, and Sales Audit partnership
• •Understanding of order lifecycle platforms including Cart & Checkout, eCommerce web, Mobile iOS/Android, AOS, SolePanel/ACT, Athlete Order, Fulfillment/Omni Shopping, Shipping, returns, and post-order adjustments
• •Understanding of operational resilience and engineering excellence tools including Grafana dashboards, LinearB, C4 and Miro architecture/process views, SLA/SLO and observability practices, automated testing, and POC-to-implementation readiness
• •Proficiency in product management, planning, and delivery tools including Aha! Roadmaps, Jira, Agile ceremonies, integrated roadmaps, backlog refinement, sprint planning, demos, retrospectives, release and validation plans
• •Definition and evolution of a roadmap for Digital Fraud in close collaboration with technology peers, Digital Loss Prevention, Payments, eCommerce, Cart & Checkout, Mobile, Athlete Order, Treasury, Sales Audit, Security, and other stakeholders
• •Establishment of metrics and measurements for the Digital Fraud product domain to report on value delivered and inform roadmap prioritization
• •Use of leading and lagging indicators such as fraud loss, chargebacks, manual review rate, cancel trends, order volume, accept/reject/review mix, false positives, SLA/SLO impacts, demand-to-fulfillment outcomes, and operational workload to guide product iteration and trade-off decisions
• •Partnership with Data Product, Analytics, Engineering, Digital LP, and business stakeholders to improve data quality, reporting, root-cause analysis, and proactive trend identification
• •Aid in formulation of hypotheses and coordination of pilots, proofs of concept, prototypes, vendor evaluations, and research that validate whether new fraud capabilities reduce business risk while preserving athlete conversion and experience
• •Evaluation of device fingerprinting, pre-authorization fraud checks, secondary fraud review, reject/recycle flows, chargeback automation, and enhanced order or athlete signals
• •Management of the backlog including creation of effective user stories, lead backlog prioritization and management, validation with engineers, product testing, acceptance criteria verification, bug capture, and defect resolution
• •Strong dependency management across payment processing, order placement, fulfillment, loyalty, customer service communications, Digital LP workflows, vendor integrations, and peak-season operational readiness
• •Creation and communication of release plans, risk assessments, go/no-go criteria, production validation plans, and operational readiness details for changes affecting fraud decisioning or athlete order flow
• •Active participation in standups, planning sessions, demos, retrospectives, stakeholder touchpoints, monthly portfolio or business syncs, and vendor discussions
• •Acting as a translator between business risk, operational workflows, technology constraints, fraud controls, analytics, and athlete experience outcomes
• •Building and maintaining the Digital Fraud roadmap collaboratively based on measurable business and technology outcomes
• •Prioritization of fraud capabilities and platform improvements aligned to fraud prevention, athlete trust, conversion, operational efficiency, and resiliency
• •Use of KPI evidence to weigh tradeoffs such as false positives, fraud loss, chargeback reduction, approval rates, SLA impact, and engineering capacity
• •Clear explanation of why work was prioritized
• •Leading discovery exercises with Digital LP, Payments, eCommerce, Cart & Checkout, Mobile, Athlete Order, Store Ops, Treasury, Sales Audit, Security, Engineering, and vendors
• •Use of fraud, payment, order, device, account, chargeback, customer service, and operational data to identify pain points
• •Monitoring of production issues, manual review trends, cancels, chargebacks, and emerging fraud trends
• •Conduct of market and vendor research
• •Prioritization based on value, risk, capacity, dependencies, and timing
• •Definition of KPIs and product objectives in collaboration with business and technology stakeholders
• •Measurement of adoption, usage, operational workload, risk reduction, fraud loss, chargebacks, manual review, order flow, and business impact of launches to prove ROI
• •Use of evidence-based influencing skills and building reporting narratives that connect delivery to measurable outcomes and leadership decisions
• •Conduct of stakeholder identification workshops and maintenance of stakeholder maps for Digital Fraud capabilities, vendor touchpoints, business owners, and technology dependencies
• •Creation and communication of standard touchpoints with Digital LP, Payments, Sales Audit, Treasury, eCommerce, Cart & Checkout, Mobile, Athlete Order, Security, and other impacted teams
• •Building shared understanding of Digital Fraud's role in the order lifecycle so teams engage early and minimize unplanned work
• •Translation of fraud-risk needs into actions for business, engineering, analytics, and vendors
• •Proactive identification of dependencies and mitigation of risky assumptions across systems, vendors, business processes, and peak readiness
• •Identification and communication of shipping risks including athlete experience, conversion, SLA, operational workload, resiliency, and compliance considerations
• •Building of release plans that clarify who is impacted, what changes, when it launches, how it will be validated, and how production outcomes will be monitored
• •Building of story maps and user stories that articulate required fraud signals, integrations, decisioning logic, data flows, and operational workflows
• •Performance of validation for releases, bug fixes, vendor integrations, fraud rules, and feature requests
• •Troubleshooting of defects and participation in root-cause analysis
• •Collaboration with third-party vendors on day-to-day activities to ensure successful product experience