Design Research Lead - Manager Level

Capital One Capital One · Banking · McLean, VA +2

This role focuses on building and utilizing AI agents and research platforms to accelerate learning velocity and build cumulative user intelligence within an enterprise setting. The primary goal is to shift from discrete UX studies to structured, connected research efforts, enabling product teams to access user insights and support the development of useful and usable experiences.

What you'd actually do

  1. Plan and conduct connected studies and establish data acquisition mechanisms that contribute to a collective body of user intelligence that fuels product teams’ ongoing planning and decision-making.
  2. Utilize and evolve research agents and research platforms to accelerate learning velocity: extracting insights from existing intelligence repositories, conducting rapid discovery, concept, content, and usability testing.
  3. Partner with research ops to enable product teams to access their users to maximize empathy and understanding.
  4. Partner with CX, data scientists, analysts, and designers to identify domain-specific UX metrics.
  5. Utilize behavioral analytics, quantitative data, and qualitative insights to produce actionable insights.

Skills

Required

  • User Experience Research, Data Science, and/or Customer Experience Research
  • aggregating, collecting, and analyzing quantitative and qualitative data
  • leading complex, multi-stakeholder projects or research programs

Nice to have

  • User Intelligence, Human Factors, or behavioral data analysis
  • conducting structured, quantitative jobs to be done studies
  • building automated research workflows
  • triangulating multiple data sources (behavioral analytics, survey data, and primary research) to inform product roadmaps
  • Advanced degree in Human Factors, HCI, Statistics, Data Science, and/or Behavioral Economics

What the JD emphasized

  • structured, systems-oriented human intelligence system
  • structured, connected research efforts
  • cumulative user intelligence
  • accelerate learning velocity
  • rapid testing
  • extracting insights from existing intelligence repositories
  • rapid discovery
  • structured, quantitative jobs to be done studies
  • automated research workflows
  • triangulating multiple data sources

Other signals

  • utilize AI agents/skills
  • structured, connected research efforts
  • build cumulative user intelligence
  • extracting insights from existing intelligence repositories
  • conduct rapid discovery, concept, content, and usability testing