Technical Product Manager - Fraud

About the role

We are seeking a highly hands-on and technical Product Manager for our Fraud team to lead the building, unification, and aggressive scaling of our next-generation risk platform.

Responsibilities

• Define & Execute Risk & Fraud Product Strategy – Work with Risk leadership to develop and own the Risk Product roadmap, focusing on unifying disparate fraud domains into a single, scalable platform for detection, prevention, and other risk management capabilities. This requires a platform-first, reusable component mindset.
• Hands-On Data Analysis & Experimentation – Own fraud metrics and have a hands-on relationship with the data. You must be able to navigate complex dashboards, run simple to medium-complexity SQL queries to validate initial hypotheses, and work with Risk Data Analysts and Data Scientists. You will be responsible for designing, setting up, and interpreting non-trivial A/B tests to ensure statistically valid and impactful outcomes.
• Fraud Detection & Prevention – Partner directly with engineering teams to design, build, and deploy advanced real-time fraud detection models, identity verification, and transaction monitoring systems.
• Cross-Functional Collaboration – Work closely with Data Scientists, Risk Analysts, engineers, and other internal stakeholders to develop scalable solutions.
• Optimize Customer Experience – Balance optimum customer experiences with effective risk mitigation strategies.
• Stakeholder Management – Communicate Risk, Product strategies, and impact to executive leadership, legal teams, and external partners.

Requirements

• 5+ years of experience in product management, with a focus on risk, fraud, payments, or trust & safety, ideally in a fast-paced startup or growth environment where you were a primary builder.
• Proven technical fluency & resourcefulness – ability to work with engineering teams on API-based fraud prevention solutions, demonstrated ability to run simple SQL queries, and a clear understanding of data pipelines and system resilience (e.g., timeouts, service dependencies).
• Deep understanding of fraud prevention techniques (e.g., device fingerprinting, behavioral analytics, transaction monitoring) or a track record of rapidly acquiring deep domain knowledge in a new technical area.
• Experience working with machine learning models and the ability to analyze fraud metrics, trends, and risk signals to drive product improvements.
• Experience working with fraud & risk tools (e.g., Riskified, Sardine, etc).
• Strong ownership and a bias towards action; we need a builder willing to take on significant individual contributor work.
• Strong stakeholder management and communication skills, especially with legal, compliance, and exec teams.
• Passion for fintech and digital finance innovation.