Mixed Methods UX Researcher – Sports

Staff Mixed Methods UX Researcher - Sports

United Kingdom

We are on a mission to pioneer the world’s next era of play. As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day.

As the Staff Qualitative Researcher is Super's most senior practitioner of human‑centred inquiry. This is a hands‑on, high‑output individual contributor role — the person who knows how to get to the truth of a user's experience: their mental models, their anxieties, their unspoken expectations, their moments of delight and frustration. You will lead qualitative research across the most strategically important and ambiguous product questions Super faces, working closely with the Principal Quant Researcher and the Research Manager to ensure qualitative and quantitative evidence are always richer together than apart.

• Design and independently execute complex, multi‑method qualitative research programmes spanning generative discovery, concept exploration, and evaluative depth — not just individual studies but longitudinal programmes of inquiry
• Lead the most high‑stakes and ambiguous research briefs: new market entry, new product category launches, trust and safety research, responsible gambling insights, and strategic bets where the organisation has the least existing evidence
• Operate the full qualitative toolkit with mastery: semi‑structured and unstructured in‑depth interviews, contextual inquiry and ethnographic observation, diary studies and longitudinal panels, participatory design workshops, focus groups, co‑creation sessions, and remote moderated/unmoderated studies
• Own recruitment strategy end‑to‑end: define screeners, work with research ops and vendors, build proprietary panels where needed, and ensure participant samples are representative of the diversity of Super's user base across markets
• Produce analysis that goes beyond surface themes, applying systematic coding, grounded theory approaches, interpretive phenomenological analysis, or jobs‑to‑be‑done frameworks — selecting the analytical lens that fits the question

• Lead the integration of AI tooling into Super's qualitative research practice as a force multiplier that increases throughput and analytical depth
• Deploy LLM‑assisted transcript analysis pipelines that handle first‑pass thematic coding, anomaly flagging, and cross‑participant pattern detection — freeing analyst time for higher‑order interpretation
• Use AI tools for rapid synthesis across large corpora of qualitative data: customer feedback, support tickets, app reviews, social listening, and interview transcripts
• Critically evaluate the output of AI‑assisted analysis for bias, hallucination, and over‑compression, maintaining methodological integrity whilst embracing efficiency
• Build workflows and documentation that allow the broader team to use AI‑assisted qualitative tools responsibly, and run training sessions that upskill colleagues on both the power and the limits of these tools

• Translate raw qualitative data into insight frameworks that have a life beyond the single study: mental model maps, user need taxonomies, experience principles, and behavioural archetypes that inform multiple product teams over multiple quarters
• Craft research deliverables that move people — evidence‑driven narratives that make stakeholders genuinely see the world through the user's eyes
• Partner with the Principal Quant Researcher to design mixed‑methods programmes where qualitative findings generate hypotheses that quant can test at scale, and where quant anomalies trigger qualitative investigation
• Present research to senior and executive stakeholders with confidence and authority, handling pushback on findings and advocating for the user even when their experience is inconvenient…