Staff Product Manager, Risk Platform

Plaid Plaid · Fintech · San Francisco, CA · All Departments

Staff Product Manager for Plaid's internal network-health and risk platform, focusing on detecting, scoring, and acting on risky traffic across integrations. The role involves setting the roadmap, defining decisioning frameworks, and partnering with Data Science and MLE teams to improve detection precision and balance network quality with business impact. Requires hands-on data analysis and experience with ML-based products and risk models.

What you'd actually do

  1. 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.
  2. Build and own the data-driven framework for real-time block-vs-allow decisions, balancing network quality against customer and commercial impact.
  3. Aggregate requirements across risk engineering, fraud & abuse operations, and data partners into a single prioritized roadmap.
  4. Define how to measure Network Health
  5. You define and own the team’s OKRs (risky-traffic detection/step-up; ATO reduction, Authentication correctness).
  6. 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.
  7. 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.
  8. Span multiple risk problem categories simultaneously: data-partner supply risk, authentication risk/correctness, and AQO — owning one coherent roadmap across all three.

Skills

Required

  • product management
  • internal risk platforms
  • trust & safety platforms
  • fraud platforms
  • identity platforms
  • detection signals
  • precision/recall tradeoffs
  • light data analysis
  • light data investigation
  • building ML based products
  • building ML based insights
  • partnership with Data Science teams
  • partnership with MLE teams
  • risk models
  • risk decisioning
  • KYC
  • synthetic/stolen-identity detection
  • ATO

Nice to have

  • sophisticated internal risk org at a large fintech/bank/marketplace
  • former risk analyst
  • former DS
  • former investigator who moved into PM
  • familiarity with bank data
  • familiarity with open finance

What the JD emphasized

  • 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.

Other signals

  • internal risk platform
  • detection, scoring, and real-time decisioning
  • ML based products / insights
  • risk models
  • risk decisioning