Strategist, Applied Intelligence

This is a hands-on role for an early-career strategist or analyst who wants to build expertise at the intersection of experience strategy, audience research, measurement, evaluation and Answer Engine Optimisation (AEO). The role covers both traditional digital products (websites, apps) and generative, AI-driven experiences, as part of a team working out how to make these systems measurable, testable and continuously improvable. The role is based in London and requires in-office collaboration three days per week: Wednesday, Thursday, and one additional day of your choice. Candidates must be located in the London area or willing to relocate before their start date.

Responsibilities

Pull together audience research by gathering and synthesising market research and user insights to help build personas and understand user intent; Run AEO audits using established methods, documenting where brand content is missed, misread or misrepresented by AI systems and answer engines; Support experience strategy by turning audience research and user insights into product recommendations and contributing ideas in ideation sessions; Score AI outputs by applying evaluation rubrics for accuracy, brand alignment and intent-fulfilment, and flag where rubrics could be improved; Assist with testing by setting up synthetic test scenarios, analysing results, and surfacing edge cases, failure modes and patterns; Work with structured data to map brand content to semantic data models and JSON-LD schema; Track operational metrics such as latency, cost, accuracy and hallucination rate against evaluation benchmarks; Build dashboards and scorecards to maintain evaluation metrics and draft initial findings for review; Review system behaviour by checking AI outputs and system prompts against evaluation results; Prepare reporting by turning data and insights into clear charts, summaries and slides for clients and stakeholders; Collaborate with data engineering, creative and technology teams

Requirements

Experience of 2–3 years in research, analytics, measurement, marketing sciences or a related field; Research foundations, including qualitative or quantitative research methods such as surveys, interviews, desk research or audience analysis; Strategic interest in product, CX or UX strategy, and in how audience insight informs product and channel decisions; Technical basics, such as working knowledge of SQL, Python or similar for data analysis, or strong spreadsheet skills; AI curiosity and hands-on familiarity with LLM platforms (ChatGPT, Claude, Gemini, Perplexity); Data comfort when working with data in different forms, including JSON, and turning it into clear charts and summaries; Visual tools experience using Figma, Miro, Lucidchart or similar; Clear communication skills, including explaining findings to colleagues from different disciplines

Nice to have

Exposure to AI evaluation or observability tools such as LangSmith or Arize; Awareness of agentic workflows or orchestration frameworks such as LangChain or LlamaIndex; Familiarity with prompting techniques such as Chain-of-Thought and Few-Shot; Some grounding in A/B testing, experiment design or basic statistical methods; Exposure to schema markup, JSON-LD, databases or knowledge graphs; Experience with SEO or content work and interest in how it applies to answer engines; Exposure to generative AI products or evaluation