Staff Experience Designer, Risk Intelligence Platform

PayPal PayPal · Fintech · San Jose, CA +1 · Experience Design

This role focuses on designing user experiences for an AI/ML-powered Risk Intelligence Platform at PayPal. The Staff Experience Designer will create self-serve tools and dashboards to help risk and data teams detect, prevent, and respond to fraud in real time. The role involves translating complex ML capabilities into intuitive interfaces for both technical and non-technical users, simplifying technical workflows, and improving data discoverability and operational efficiency.

What you'd actually do

  1. Lead the design of self-serve tools and dashboards that help PayPal’s risk and data teams detect, prevent, and respond to fraud in real time
  2. Translate complex AI and machine-learning workflows into intuitive, transparent, and trustworthy user experiences
  3. Collaborate with product, engineering, and data science partners to shape platform strategy and deliver high-quality design outcomes
  4. Simplify technical workflows by improving data discoverability and operational efficiency across teams
  5. Design frameworks and interaction patterns that make AI insights actionable for both technical and non-technical users

Skills

Required

  • 8+ years of experience in product design, with a focus on complex systems or enterprise tools
  • Expertise in systems thinking, workflow design, and simplifying complex processes
  • Strong collaboration skills with cross-functional partners in product, engineering, content, research, and data science
  • Portfolio demonstrating excellence in end-end design, from strategy and prototyping to high-quality execution
  • Strong communication and storytelling skills to influence both technical and executive audiences

Nice to have

  • Champion usability, explainability, and human-centered principles
  • Contribute to PayPal’s design systems and best practices to ensure consistency and scalability across internal platforms

What the JD emphasized

  • complex machine-learning capabilities
  • complex workflows
  • complex systems
  • simplifying complex processes