Staff Market Intelligence Researcher

• Medical / Health Insurance
• Open Annual Leave
• Employee Assistance Programme
• Training & Learning Development

Additional benefits vary by country and will be shared during the hiring process.

• 6-9 years in consumer insights or market research with strong mixed-methods expertise.
• Proven experience building and running AI-augmented research workflows at scale.
• Track record of operating in high-throughput, fast-paced environments.
• Strong quantitative skills across survey design, sampling, and analysis.
• Solid qualitative expertise including moderation, discussion design, and synthesis.
• Experience with brand tracking or continuous measurement systems.
• Commercial acumen - ability to connect insights to business outcomes.
• Background in fast-moving digital consumer businesses such as gaming, e-commerce, or fintech.

• Experience in gaming, sports betting, or high-LTV consumer sectors.
• Familiarity with tools such as Brandwatch, Klue, Quantilop, Crayon, or similar.
• Experience with AI research platforms, such as AI-moderated interviews or qualitative synthesis tools.
• Exposure to synthetic research methods including AI personas and simulated respondents.
• Coding experience in Python or R for automation or analysis.
• Multi-market or international research experience.

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.

Traditional market research is built around studies. This role is not. At Super, we are building an AI-native research function where insight is not delivered in isolated projects, but generated continuously through systems. As a Staff Market Intelligence Researcher, your primary tool is AI - not as a shortcut, but as the infrastructure through which research happens.

You will design and operate research systems that produce high-quality consumer and market intelligence at a speed and scale that traditional agency models cannot match. This is a hands-on, high-impact individual contributor role sitting across Marketing Intelligence and Performance & Analytics, connecting consumer understanding directly to commercial outcomes whilst building the workflows, tools, and infrastructure that make this possible.

Building AI-native research systems

• Design and run AI-moderated qualitative research at scale, including interviews, concept testing, and exploratory qual.
• Build repeatable workflows: survey pipelines, social listening synthesis, and competitive monitoring agents.
• Use LLMs to analyse large volumes of unstructured data such as app reviews, transcripts, and customer feedback.
• Implement validation frameworks to ensure AI outputs are reliable and decision-ready.
• Optimise every workflow for speed, with most outputs delivered in days, not weeks.

Delivering high-throughput insight

• Own and triage research requests from across the marketing organisation.
• Deliver insights within a two-week maximum turnaround, often faster for urgent needs.
• Translate findings into clear, actionable recommendations for marketing teams.
• Run both synthetic-first validation and targeted human research where required.

Owning always-on consumer & brand intelligence

• Operate a continuous brand intelligence system covering pulse surveys, sentiment, and social data.
• Maintain and evolve consumer segmentation frameworks.
• Conduct deep qualitative research for complex or high-stakes questions.
• Build and manage a structured, searchable insights library.

Building automated competitive intelligence

• Deploy automated agents to track competitor activity across ads, pricing, hiring, product, and media.
• Synthesise signals into regular, decision-oriented competitive briefings.
• Interpret what competitor activity means - not just what happened.

Developing AI research infrastructure

• Own the AI research tool stack: evaluation, integration, and governance.
• Create automated pipelines for intake, sampling, analysis, and delivery.
• Establish best practices for responsible, rigorous AI-assisted research.
• Stay ahead of emerging methodologies such as synthetic research, agentic workflows, and multimodal analysis.

Connecting insight to commercial impact

• Partner with analytics to explain performance trends through consumer understanding.
• Feed insight into campaign development - not just post-campaign evaluation.
• Contribute to leadership-level marketing intelligence reporting.