Define the quantitative research strategy for AI-powered product areas, establishing how we measure the quality, trust, and effectiveness of intelligent systems at scale.
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.
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.
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.
Partner with other Researchers, AI/ML scientists, Data Science, Product, and Design to embed human-centered measurement into AI development workflows and evaluation pipelines.
Mentor researchers across the team and contribute to thought leadership in AI evaluation, raising the bar for quantitative rigor both internally and in the broader community.

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.

Principal Quantitative User Experience Researcher, AI

Key skills