Lead Product Manager, Risk Decisioning

Essential Responsibilities: Inputs to product strategy with cross-functional stakeholders consistent with the shared vision for the product or enabling platform. Implements the architectural roadmap that balances innovative design and technical implementation, while balancing regulatory requirements, time-to-market, meeting customer needs and product profitability. Controls for the customer experience and customer needs in product requirements and as an input to decision making. Monitors metrics that inform the success of products including usability studies, research and market analysis. Manages one or more workstreams to include analytics, customer discovery, market research and competitive analysis to drive data-driven decision-making. Monitors product profitability measures, including budget. Participates in operational mechanisms that drive execution and accountability including Product Reviews, Operating Reviews, and Business Reviews. Interfaces with product and technology leadership as needed. Partners with content developers, data scientists, product designers and user experience researchers.

Minimum Qualifications: 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Additional Responsibilities & Preferred Qualifications :Experience building products in fraud, account integrity, credit, or other risk domains, in close partnership with risk strategy teams. Track record of setting a multi-year product vision and roadmap, balancing near-term delivery with longer-term bets. Working knowledge of how risk decisions are made and tuned, including rules, ML models, features, and step-up and friction treatments, and the tradeoff between loss and customer experience. Strong quantitative skills: defining and interpreting risk metrics (loss, catch, false positive, and approval rates), sizing opportunities, and connecting product changes to business impact. Experience launching through controlled rollouts and experimentation, including champion/challenger tests and staged traffic ramps. Experience translating business needs into clear asks for data science, modeling, and platform teams, and managing dependencies across them. Experience leading major platform transitions, such as migrating risk strategies off legacy systems, while protecting performance. Ability to influence senior business stakeholders and drive milestone-based delivery across multiple teams.