Senior UX Research Manager

As Senior UX Research Manager at Super, you will own and scale a high-impact research function that sits at the heart of every major product decision. This is not a purely strategic or administrative role - we are looking for a hands-on research leader who can manage and grow a large team while simultaneously being a credible, practicing researcher. You will report to the Research Director and have a direct seat at the executive table, shaping product strategy through the voice of the user. You will be expected to leverage AI tooling to transform how research is conducted, synthesized, and actioned across the organisation. This role defines the future of UX Research at Super.

• Define and own the multi-year UX research strategy aligned to Super's product and business goals across sports betting, gaming, and payments verticals.
• Translate ambiguous business challenges into crisp research programmes that generate confident executive decisions - from market expansion and feature prioritisation to onboarding flows and live betting experiences.
• Build and maintain a research roadmap that balances generative discovery, evaluative testing, and longitudinal tracking at scale.
• Represent research at the executive and C-suite level, presenting insights that drive resource allocation, product pivots, and go-to-market strategy.
• Directly manage and grow a team of 6-8 UX researchers across seniority levels (junior through staff), spanning qual, quant, and mixed-methods disciplines.
• Grow junior managers in both UX Research and Market Research
• Maintain a hands-on presence: you conduct research yourself, review screeners and discussion guides, and are present in sessions - not only in deck reviews.
• Build a culture of craft and rigor; personally mentor researchers on methodology selection, analysis quality, and storytelling.
• Own hiring, performance management, career development frameworks, and team structure - adapting org design as the team scales.
• Create psychological safety and high-output norms simultaneously: a team that ships great research fast and keeps raising the quality bar.
• Lead the transformation of Super's research workflows through AI: identify, pilot, and embed AI tools for participant recruitment, auto-transcription and synthesis, pattern recognition across data sets, and accelerated insight generation.
• Champion AI-assisted analysis (e.g., LLM-powered thematic coding, sentiment analysis across user feedback pools) to reduce time-to-insight without sacrificing rigour.
• Establish responsible AI use guidelines for research — ensuring synthetic data, simulated users, and AI-generated summaries are used critically and transparently.
• Partner with data science and analytics to build continuous research intelligence pipelines that surface user signals in near-real-time.
• Stay ahead of the curve on AI-native research methods (e.g., conversational research agents, automated usability benchmarking) and make evidence-based bets on adoption.
• Operate as a trusted advisor and thought partner to the VPs Product, and VP Design - shaping strategic decisions with user evidence before options narrow.
• Design and deliver research artefacts calibrated for executive consumption: crisp, opinionated, and actionable - not exhaustive reports, but decision-accelerating briefs.
• Build a culture of evidence-based decision-making across Product, Engineering, Marketing, and Commercial teams by embedding research touchpoints in planning and OKR cycles.
• Proactively identify decisions being made without research and intervene diplomatically with the right methodology at the right fidelity.
• Build and own the research operations infrastructure: panel management, vendor relationships, consent frameworks, data governance, and tooling stack (e.g., Dovetail, UserZoom, Lookback, Maze).
• Establish a shared research repository that makes insights discoverable and reusable across product teams.
• Develop research democratisation programmes — training product managers and designers in appropriate self-serve methods while protecting methodological integrity.
• Define quality standards and peer-review practices that elevate the output of every researcher on the team.

• 10+ years of UX research experience in high-growth product environments, with at least 5 years in a people management role.
• Demonstrated experience managing large research teams (6+ direct and indirect reports) in a fast-paced, matrixed organisation.
• Proven track record of conducting and leading both qualitative and quantitative research — you are as comfortable running a contextual inquiry as you are designing a quant survey instrument.
• Experience presenting research to C-suite and board-level stakeholders and influencing major product or business decisions.
• Hands-on experience implementing AI tooling in research workflows — not just awareness, but actual deployment and change management.
• Strong command of the full research methods toolkit: ethnographic research, diary studies, usability testing, concept testing, conjoint analysis, surveys, behavioural analytics, and more.
• Hands-on by default: You don't delegate everything. You know what good research looks like because you still do it.
• Executive presence: You can distill six months of research into a three-slide brief that changes a product direction.
• AI-native: You have moved beyond experimenting with AI tools and are actively building AI into your team's operating model.
• Systems thinker: You see research not as isolated studies but as an interconnected evidence system that continuously informs strategy.
• People developer: You have a track record of researchers growing significantly under your leadership.
• Commercially literate: You connect user insights to business outcomes — revenue, retention, conversion, and lifetime value — and speak that language fluently to non-research stakeholders.
• Comfortable with ambiguity: You thrive in environments where the brief is unclear, the timeline is compressed, and the stakes are high.
• Experience in betting, gaming, fintech, or other high-velocity consumer product environments.
• Academic background in HCI, Psychology, Cognitive Science, Sociology, or a related human behaviour field.
• Experience building research practices from scratch or in significant transformation phases.
• Fluency in data tools (SQL basics, Tableau, Amplitude, Mixpanel) to triangulate behavioural with attitudinal data.
• Experience with internationalisation research across multiple markets and cultures.