Senior Product Manager – Risk Decisioning Platform

PayPal PayPal · Fintech · San Jose, CA +1 · Product Management

Product Manager for PayPal's Risk Decisioning Platform, focusing on real-time fraud, credit, and compliance decisions. The role involves gathering requirements, partnering with engineering and data science, and managing a core platform pillar that processes massive signal volumes in milliseconds. Experience with scaled platforms like recommendation engines or ML inference infrastructure is desired.

What you'd actually do

  1. Uses data to build insights on product or platform requirements consistent with the shared vision for the product.
  2. Gathers insights from the customer experience and customer needs to input to product requirements
  3. Analyzes research, market analysis and usability studies, research and market analysis to support data-driven decision making
  4. Monitors product profitability measures, including budget.
  5. Lead sprint planning, daily standups and retrospectives to drive execution. Interfaces with product and technology leadership as needed.

Skills

Required

  • 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

Nice to have

  • Exposure to decisioning platforms, recommendation systems, feature stores, rule engines, or real-time ML inference infrastructure.
  • Experience supporting platform adoption across multiple internal teams, including managing competing requirements and negotiating prioritization.
  • Ability to define and track platform KPIs and translate data insights into actionable product decisions.
  • Familiarity with agile methodologies, including backlog management, sprint ceremonies, and milestone tracking.
  • Strong written and verbal communication skills; able to translate technical complexity into clear narratives for both engineering and business stakeholders.

What the JD emphasized

  • real-time ML inference infrastructure

Other signals

  • real-time decision-making
  • processing massive signal volumes in milliseconds
  • core platform pillar
  • fraud, credit, and compliance decisions
  • scalable solutions
  • faster experimentation
  • real-time feature access
  • recommendation engines
  • inference systems
  • ML/AI
  • decisioning platforms
  • real-time ML inference infrastructure