Staff Product Manager, Risk Platform

About the Role

As a key member of the risk engineering team, the Staff Product Manager will aggregate requirements across risk engineering, fraud & abuse operations, and data partners into a single prioritized roadmap. This role requires a deep understanding of risk management, product development, and data analysis, as well as excellent communication and collaboration skills.

The team at Plaid is dedicated to empowering the transformation of financial interactions, and this role plays a crucial part in that mission. By protecting the integrity of Plaid's network and authentication surfaces, the Staff Product Manager contributes to the company's goal of unlocking financial freedom for everyone.

What You Will Do

• Define and prioritize the DS/MLE roadmap for network-health detection, focusing on model investment needs and precision/recall tradeoff decisions.
• Build and own the data-driven framework for real-time block-vs-allow decisions, balancing network quality against customer and commercial impact.
• Aggregate requirements across risk engineering, fraud & abuse operations, and data partners into a single prioritized roadmap.
• Define how to measure Network Health, setting clear, data-backed thresholds for when to allow, step up, or block traffic.
• Get hands-on with data, running light investigations, pulling signals, and grounding product decisions in evidence.
• Span multiple risk problem categories simultaneously, including data-partner supply risk, authentication risk/correctness, and AQO.
• Define and own the team’s OKRs, focusing on risky-traffic detection, step-up, ATO reduction, and authentication correctness.
• Define and recommend Plaid’s risk-versus-conversion posture, partnering with company leadership to set clear thresholds.
• Collaborate closely with the Data Science and MLE teams to sharpen detection precision and ensure platform trustworthiness.

What We Are Looking For

• 6+ years of experience in product management, ideally in internal risk, trust & safety, fraud, or identity platforms.
• Hands-on technical depth, including detection signals, precision/recall tradeoffs, and light data analysis/investigation.
• Experience building ML-based products or insights, with a strong understanding of risk models and decisioning frameworks.
• Proven partnership with Data Science/MLE teams on risk models, with the ability to articulate model needs and translate outputs into product actions.
• Experience with risk decisioning, KYC, synthetic/stolen-identity detection, or ATO, and a deep understanding of risk management principles.
• Clear product requirements and strong cross-functional alignment, with the ability to communicate complex technical concepts to non-technical stakeholders.
• Experience working in a fast-paced, dynamic environment, with a focus on delivering high-quality results under tight deadlines.

Nice to Have

• Experience in a sophisticated internal risk organization at a large fintech, bank, or marketplace.
• Former risk analyst/DS/investigator who moved into product management, with familiarity with bank data and open finance.
• Knowledge of regulatory requirements and industry standards for risk management and compliance.
• Experience with cloud-based technologies and agile development methodologies.

Benefits and Perks

• Competitive salary and equity package, with opportunities for career growth and professional development.
• Comprehensive health insurance, including medical, dental, and vision coverage.
• Flexible PTO policy, with a focus on work-life balance and employee well-being.
• Remote work stipend, with opportunities for flexible and remote work arrangements.
• Access to cutting-edge technologies and tools, with ongoing training and professional development opportunities.
• Collaborative and dynamic work environment, with a focus on innovation and teamwork.

• Develop a strong understanding of risk management principles, including detection, scoring, and decisioning frameworks.
• Highlight your experience working with Data Science and MLE teams, and your ability to articulate model needs and translate outputs into product actions.
• Be prepared to discuss your hands-on technical depth, including detection signals, precision/recall tradeoffs, and light data analysis/investigation.
• Showcase your ability to communicate complex technical concepts to non-technical stakeholders, and your experience working in a fast-paced, dynamic environment.
• Research Plaid's mission and values, and be prepared to discuss how your skills and experience align with the company's goals and objectives.
• Prepare examples of your experience working with risk decisioning, KYC, synthetic/stolen-identity detection, or ATO, and your understanding of regulatory requirements and industry standards.
• Highlight your experience working in a sophisticated internal risk organization, and your familiarity with bank data and open finance.