Senior Product Manager, Fraud Risk Platforms

New

JobgetherFraud risk technology

Fully remote opportunity within the United States.Full-TimeSenior

SalaryUS base salary range of $136,000–$170,000. Eligibility for additional bonus and equity compensation.

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Job Details

Hold a bachelor’s degree or have an equivalent combination of education, professional experience, and training.
Have 7+ years of product management experience and a strong track record of owning strategy and delivering complex products.
Have experience in fraud, risk, trust and safety, or large-scale operational automation environments.
Demonstrate the ability to define product strategy, develop roadmaps, and lead initiatives from discovery through delivery and iteration.
Use analytical, data-driven decision-making, including defining KPIs and evaluating product performance.
Have experience collaborating across Engineering, Data Science, Analytics, Operations, Compliance, and business teams.
Bring understanding of automation, AI-assisted decisioning, risk operations, case management, or foundational technology platforms.
Operate effectively in ambiguous environments and balance strategic objectives with immediate operational needs.
Demonstrate communication, stakeholder management, and influencing skills, including engagement with senior leaders.
Show ownership and customer orientation, and the ability to understand user needs and turn operational challenges into effective experiences.
Experience in a regulated sector such as gaming, fintech, payments, or insurance is a plus.

Own and execute an outcome-driven roadmap for fraud and risk case decisioning across AI-assisted review, automation, customer self-service, and case management.
Partner with Risk Operations to understand workflows, identify pain points, and prioritize opportunities using performance data.
Define resolution paths for cases, including automation, AI-assisted handling, self-service, and escalation to human review.
Shape the case lifecycle, including case types, states, routing, prioritization, queues, resolution actions, closure criteria, and supporting evidence.
Lead product discovery and delivery with Engineering, Data Science, Analytics, Controls & Compliance, and other cross-functional teams.
Translate business and operational needs into product requirements, acceptance criteria, measurable outcomes, and roadmaps.
Establish success metrics and analyze automation rates, workload reduction, self-service containment, AI review quality, decision quality, and operational costs.
Assess the operational impact of upstream risk model, orchestration, and tooling changes before they reach operational teams.
Build auditability into automated and AI-supported decisions, including decision rationale and supporting evidence.
Influence stakeholders and cross-functional teams on priorities, trade-offs, investment decisions, and business outcomes.

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