UX Survey Scientist

About the role

Client is building an insights repository that will serve as the quantitative backbone of an Al-powered research intelligence system. We are looking for a Survey Research Scientist to own the quantitative research workstream and ensure survey best practices are established and scaled across the team.

Responsibilities

• Design and validate quantitative research instruments, ensuring surveys are reliable, unbiased, and measure what they claim to measure
• Develop and maintain a library of validated, reusable scales for core constructs enabling consistent measurement across studies and over time
• Lead the design and statistical validation of client segmentation frameworks using latent class analysis, factor analysis, and cluster analysis
• Conduct inferential statistical analysis across quantitative datasets, including significance testing, regression modeling, and advanced preference measurement (MaxDiff, conjoint)
• Define and enforce confidence standards for the insights repository establishing clear thresholds for when a finding is statistically significant vs. directional, and ensuring those distinctions are applied consistently
• Partner with qualitative researchers and behavioral analysts to ensure quantitative studies are grounded in prior exploratory insight and that findings are structured for integration into a shared, Al-augmented repository

Requirements

• Education: Master's degree or PhD in Psychology, Statistics, Cognitive Science, Sociology, or a related quantitative field
• Technical Skills: Proficiency in confirmatory factor analysis (CA) and item response theory (IRT) for scale development and validation; Applied experience in sampling design, including stratified and quota-based approaches appropriate to defined target population; Hands-on experience with segmentation methodologies such as latent class analysis, factor analysis, cluster analysis, and Principle Component Analysis; Strong command of inferential statistics: regression modeling, ANOVA, and correction for multiple comparisons; Experience with advanced preference measurement: MaxDiff and/or conjoint analysis; Production-level proficiency in R or Python; familiarity with survey platforms such as Qualtrics or equivalent; Experience 8+ years of applied quantitative research experience with demonstrated ownership of full study design through analysis and insight delivery; Demonstrated experience working in a mixed-methods environment, collaborating with qualitative researchers as part of an integrated research approach; Experience with B2B, professional, or institutional audiences preferred; financial services context is an advantage but not required; Ability to communicate statistical findings clearly to non-technical stakeholders translating complexity into language that informs decisions without overstating certainty