Staff Market Intelligence Researcher

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. Where others deliver one study in six weeks, you will deliver multiple validated insights in a fraction of the time—not by working harder, but by working differently.

This is a hands-on, high-impact individual contributor role. You will sit across Marketing Intelligence and Performance & Analytics, connecting consumer understanding directly to commercial outcomes, while building the workflows, tools, and infrastructure that make this possible.

 

What You’ll Be Doing

 

Building AI-Native Research Systems

You will move research from one-off studies to continuous intelligence systems.

• Design and run AI-moderated qualitative research at scale (e.g. interviews, concept testing, exploratory qual)
• Build repeatable workflows: survey pipelines, social listening synthesis, competitive monitoring agents
• Use LLMs to analyse large volumes of unstructured data (app reviews, transcripts, 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

You will be the primary executor of research—not a coordinator.

• 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

You will build and maintain a live view of the consumer and brand.

• Operate a continuous brand intelligence system (pulse surveys, sentiment, 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

You will create a system that continuously monitors the market.

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

Developing AI Research Infrastructure

You will build the foundation that enables scale.

• 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 (synthetic research, agentic workflows, multimodal analysis)

Connecting Insight to Commercial Impact

You will bridge research with performance.

• 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

 

What We Are Looking For

• 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 (survey design, sampling, analysis)
• Solid qualitative expertise (moderation, discussion design, 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 (e.g. gaming, e-commerce, fintech)

Nice to Have

• 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 (e.g. AI-moderated interviews, qualitative synthesis tools)
• Exposure to synthetic research methods (AI personas, simulated respondents)
• Coding experience (Python or R) for automation or analysis
• Multi-market or international research experience