Staff Product Manager, Risk Modeling

Responsibilities

• Define and prioritize the DS/MLE roadmap for network-health detection — articulate model investment needs, own precision/recall tradeoff decisions, and translate model outputs into real-time product actions.
• Build and own the data-driven framework for real-time block-vs-allow decisions, balancing network quality against customer and commercial impact.
• Agregate requirements across risk engineering, fraud & abuse operations, and data partners into a single prioritized roadmap.
• Define how to measure Network Health.
• Define and own the team’s OKRs (risky-traffic detection/step-up; ATO reduction, Authentication correctness).
• Define and recommend Plaid’s risk-versus-conversion posture, partnering with company leadership to set clear, data-backed thresholds for when to allow, step up, or block traffic.
• Get hands-on with data: run light investigations yourself, pull signals, and ground product decisions in evidence — this PM doesn't wait for an analyst to tell them what's happening.
• Span multiple risk problem categories simultaneously: data-partner supply risk, authentication risk/correctness, and AQO — owning one coherent roadmap across all three.

Qualifications

• 6+ years in product management, ideally on internal risk, trust & safety, fraud, or identity platforms.
• Hands-on technical depth: detection signals, precision/recall tradeoffs, light data analysis/investigation.
• Experience building ML based products / insights.
• Proven partnership with Data Science / MLE teams on risk models.
• Experience with risk decisioning, KYC, synthetic/stolen-identity detection, or ATO.
• Clear product requirements; strong cross-functional alignment.
• [nice to have] Experience in a sophisticated internal risk org at a large fintech/bank/marketplace.
• [nice to have] Former risk analyst / DS / investigator who moved into PM; familiarity with bank data / open finance.