UK remote
Senior Quantitative UX Researcher
About this role
At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We’re a leading online reviews platform, free and open to all. Our mission is to be a universal symbol of trust.
We are well on our way - but there’s still an exciting journey ahead of us. Do you want to join us at the heart of trust? We’re currently looking for a Senior UX researcher to join our team at Trustpilot. Our goal is simple: to become the most trusted reviews platform in the world. We will achieve this by being ready and willing to disrupt ourselves through innovation, data and insight and adding product professionals with ambitions that match our own.
As Senior UX Researcher, you'll be the go-to expert on measuring how people and businesses experience trust on Trustpilot , from reading a review to deciding our platform is worth paying for. You'll own the quantitative research agenda for your product areas, set the bar for statistical rigour across the team, and partner with Data Science to build a shared measurement culture. What you'll be doing: Research strategy & execution Design and own the quantitative research roadmap for your product areas, e.g.
attitudinal measurement, behavioural analysis, and longitudinal tracking. Lead large-scale surveys (validated scales, NPS derivatives, trust-perception metrics) and log-data/behavioural analytics (funnels, A/B tests, cohort and retention modelling). Build measurement frameworks that define what ‘good’ looks like for review-reading, purchase-decision, and business-subscription journeys and track them over time. Quantitative methods Lead advanced quantitative research - surveys, behavioural analytics, experimentation, predictive modelling using statistical rigor as the throughline, from validated instrument design through to automated, auditable analysis pipelines (Python/R/SQL).
Pioneer AI-assisted techniques (e.g. LLM-assisted open-text analysis) where they genuinely sharpen the work, evaluating any AI tooling with a critical eye on validity and bias. Standards, influence and coaching Partner with Data Science and Analytics on shared definitions and data pipelines; hold the bar on study design and statistical rigour across the team. Translate statistical output into clear, decision-forcing narratives that PMs, designers, and engineers act on.