Principal Quantitative User Experience Researcher, AI

Expedia Expedia · Hospitality · Seattle, USA - New York - New York, Austin Domain 11 - HomeAway, USA - California - San Jose, WA

Expedia is seeking a Principal Quantitative User Experience Researcher to define and lead the research strategy for AI-powered product areas. This role involves creating measurement frameworks, designing surveys and behavioral studies, analyzing log data, and partnering with AI/ML teams to ensure human-centered AI development. The focus is on evaluating the quality, trust, and effectiveness of intelligent systems, including LLMs, recommendation systems, and agentic workflows.

What you'd actually do

  1. Define the quantitative research strategy for AI-powered product areas, establishing how we measure the quality, trust, and effectiveness of intelligent systems at scale.
  2. Design and execute large-scale surveys, behavioral studies, and log-data analyses — linking attitudinal data from surveys to behavioral signals from product logs to generate integrated insights.
  3. Build and validate measurement frameworks — including psychometric instruments, experience metrics, and AI evaluation rubrics — that apply statistical rigor to challenges like LLM output quality, human-in-the-loop assessment, and benchmark validation.
  4. Write and maintain complex SQL queries and Python or R scripts to access, clean, analyze, and build scalable datasets that track AI quality and experience outcomes over time.
  5. Partner with other Researchers, AI/ML scientists, Data Science, Product, and Design to embed human-centered measurement into AI development workflows and evaluation pipelines.

Skills

Required

  • Master's degree or PhD in Human-Computer Interaction (HCI), Computer Science, Statistics, Psychology, or a related field — or equivalent professional experience.
  • 8+ years with no advanced degree, or 5–10 years with a suitable advanced degree.
  • Expert in quantitative research methods: survey design and psychometrics, experimentation, key driver analysis, and hypothesis testing.
  • Expert-level SQL skills and expert-level proficiency in Python or R (or both) for statistical analysis, modeling, and data visualization.
  • Deep experience connecting survey-based attitudinal data to behavioral log data to generate integrated insights.
  • Demonstrated understanding of AI/ML systems — including how large language models, recommendation systems, or agentic workflows function — and the ability to design research that evaluates them from a human perspective.
  • Strong ability to define and operationalize metrics that are scientifically valid and meaningful to product and engineering partners, with the communication skills to make them land.

Nice to have

  • Experience designing or contributing to AI evaluation frameworks, including human evaluation protocols, LLM-as-judge validation, or automated benchmark quality assessment.
  • Familiarity with psychometric validity frameworks (construct validity, criterion validity, reliability) and their application to AI output quality measurement.
  • Experience working on generative AI, conversational AI, or agentic product experiences.
  • Background working within or alongside AI/ML teams, not just researching their outputs.
  • Experience with survey platforms (e.g., Qualtrics) and site intercept methodology.
  • Contributions to the research or AI community via publications, conference presentations, or open-source work.

What the JD emphasized

  • define the quantitative research strategy
  • measure the quality, trust, and effectiveness
  • Build and validate measurement frameworks
  • AI evaluation rubrics
  • human-in-the-loop assessment
  • AI quality and experience outcomes
  • human-centered measurement
  • AI development workflows and evaluation pipelines
  • AI evaluation
  • quantitative rigor

Other signals

  • defining how we measure human experience with AI
  • build measurement frameworks
  • AI evaluation rubrics
  • human-centered measurement into AI development workflows and evaluation pipelines