Product Manager, Ecosystem Risk

Summary

Join Stripe's Fraud organization and define the strategy and roadmap for the Fraud Assessment Engine. Drive the creation and iteration of fraud assessment models, collaborating with data teams to leverage a shared, real-time data layer. Partner with other teams to translate risk scores into concrete actions, managing trade-offs between precision and recall. Act as the voice of stakeholders in product and API designs, gathering feedback to refine assessment capabilities. Work with ML Engineers and data science teams to build scalable, real-time systems. This pivotal role protects Stripe's ecosystem from systemic risks.

Requirements

• 8+ years in Product Management, specifically in delivering exceptional user experiences for complex and technical products
• Experience managing technical software products from kick-off to ship
• Consistent track record of leading ambitious and ambiguous 0-to-1 projects
• Strong stakeholder management, including navigating difficult situations, negotiating timelines, and influencing internal and external stakeholders across organizations and borders
• Strong communications skills – you can summarize and express complex requirements in an accessible and precise manner

Responsibilities

• Define the strategy and roadmap for Stripe’s Fraud Assessment Engine, including its machine learning models, heuristic triggers, anomaly detection, and aiding in discovery of new fraud vectors
• Drive the rapid creation and iteration of fraud assessment models, constantly working to push the precision-recall frontier to enhance accuracy and efficiency
• Collaborate closely with the Data teams to add to and leverage a single, shared, real-time data layer that ingests and enriches every fact relevant for fraud assessments, eliminating siloed data and compounding network effects
• Partner with the teams up the stack to translate abstract risk scores into concrete actions, managing trade-offs between precision and recall, user experience, rewards and loss avoidance
• Partner with teams up the stack to ensure assessments inform reactive controls for risky users (e.g., blocks, holds, step-ups) and proactive feature-ungating for trusted users (e.g., higher limits, instant payouts)
• Act as the voice of internal and external stakeholders in product and API designs, gathering direct feedback to refine assessment capabilities
• Work with ML Engineers and data science teams to build scalable, real-time fraud assessment systems that embody Stripe’s operating principles: defaulting to minimum disruption, and resorting to explicit interventions only when confidence is high, because users are good until proven otherwise

Preferred Qualifications

• Preferably has experience in building real time ML systems
• Preferably has experience with Risk systems
• Experience working on fast paced teams, particularly around experimentation
• Proven experience with machine learning products, data-driven systems, and/or API platforms , particularly in risk, fraud detection, or related domains, enabling rapid model creation and iteration
• Deep understanding of fraud detection methodologies, risk scoring, or related data science concepts with an emphasis on precision and recall optimization