Staff UX Researcher

Senior-to-Staff Track Record: 8-10+ years of leading high-impact UX research at software companies, ideally in complex or multi-sided products, plus a degree in HCI, Psychology, Anthropology, Social Sciences, Data Science, or a related field (or equivalent experience).

Expert-Level Research Design: You are exemplary in at least one core research competency and strong across the rest. You know when a shortcut compromises the answer.

Mixed-Methods Fluency: Confident with qualitative (field studies, interviews, workshops) and quantitative (survey design, behavioral data, statistical reasoning) approaches, and able to combine them.

Domain Depth: Evidence that you built lasting expertise in a domain and turned it into a point of view the business used.

Executive Influence: Experience presenting to C-level, framing findings around business outcomes, and holding your position under pressure.

Strategic Impact: You have shaped roadmap-level trade-offs, not only product decisions, and can show the outcome.

Leading Through Others: You have mentored or led researchers, set shared methods, and improved research operations.

Narrative Craft: You make findings memorable and legible to people who did not run the study.

Are you the researcher leadership calls when a decision is too big to get wrong?

Do you go deep enough in a domain to become the person everyone asks, then zoom out to connect that expertise to product strategy? Do you move between a survey, a regression, a field study and a workshop without losing rigor? Can you sit with a C-level leader, hold your position, and leave with a decision?

We're looking for a Staff UX Researcher to lead our most business-critical research. You'll set the research agenda for a product area, build domain expertise that compounds over time, and lead other researchers to execute. If you want your work to shape what a customer-centric, data-informed automation platform builds next, this role is for you!

Own the highest-stakes research initiatives for a product area, from framing the strategic question to the decision it informs.

Decide what deserves rigor and what doesn't, and say no to studies that dilute the story.

Lead other researchers to execute against a shared agenda, and step in hands-on where the risk is highest.

Go deep in a domain (for example, creators, monetization, or channels) through expert research, and synthesize across studies and quarters into a durable point of view.

Spot where research is structurally missing in the product and data systems, and close the gap.

Design mixed-methods programs that triangulate behavioral data, surveys, and qualitative work into one answer.

Partner with product analysts and data science on sizing, segmentation, and measurement.

Use AI for the operator-side work (transcription, first-pass clustering, drafts) and own the interpretation the org will act on.

Present to and advise C-level and senior leaders, often to people who were not in the room.

Get research embedded in planning and roadmap trade-offs, not bolted on afterwards.

Hold an ethical line on participants and data even when it is costly to the roadmap.

Establish methods, templates, and ResearchOps decisions (tooling, panel strategy, repository structure) that other researchers adopt.

Mentor researchers and calibrate quality across the team.

Set the area's stance on AI in research: which study types can run mostly AI-assisted, which still need a human-designed protocol, and where AI tooling is trustworthy enough to scale. Build shared synthesis practices that other researchers use.

Decisions Changed: Your research shapes company and product area strategy, and leadership can point to bets that went a different way because of it.

Trusted Domain Authority: Product, design, data, and leadership come to you first on your domain, and your point of view holds up over time.

One Answer from Many Methods: Mixed-methods work replaces competing qualitative and quantitative narratives with a single recommendation.

Leadership Confidence: C-level partners rely on your judgment, and research is part of planning instead of a late check.

Raised Bar: Other researchers adopt your methods and patterns, including clear guardrails for where AI helps and where it doesn't, and the quality of research across the area goes up.