• Own the design, build, and ongoing evolution of the data models, dashboards, and reporting frameworks that give the commercial organisation clear visibility into performance across the full revenue funnel — and maintain them to a standard that makes the data genuinely trusted and acted upon. • Use AI tools as a core part of your analytical workflow — accelerating the speed of insight generation, improving output quality, and freeing up time for higher-order problem solving. • Conduct deep-dive analytical projects to identify patterns, anomalies, and opportunities in revenue data — translating complex findings into clear, actionable insights for commercial stakeholders. • Define, build, and track KPIs that measure not just business outcomes, but the effectiveness of the processes that drive them — creating a feedback loop that continuously improves how the organisation operates. • Map, challenge, and rebuild core revenue workflows — including pipeline management, forecasting cadences, and sales incentive structures — producing cleaner, faster, and more scalable ways of working. • Implement operational improvements end-to-end: not just designing the solution, but seeing it through to adoption across commercial teams and measuring its impact with rigour. • Identify where AI can be applied to fundamentally change how revenue processes work — building and deploying those solutions directly rather than outlining them for others to execute. • Develop a hands-on understanding of how our revenue tech stack — data pipeline and customer-facing product — fits together, diagnosing where friction, data loss, or missed opportunities exist. • Work directly with Product and Engineering teams to shape and prioritise improvements to internal tooling and systems, grounding those conversations in operational data and a clear point of view on what will move the needle. • Translate commercial problems into well-defined briefs that technical teams can act on — bringing enough technical fluency to be a genuine peer in those conversations.