Marketing Intelligence Lead London – hybrid (2 days in) £85,000 - £115,000 bonus & benefits A newly created role to build a marketing measurement framework that assesses the true effectiveness of marketing activity and guides where investment should be made. In this role, you’ll apply advanced analytical techniques - such as marketing mix modelling, multi‑touch attribution, econometrics, and incrementality testing - to understand which channels drive customer acquisition and how marketing contributes to sales outcomes. You’ll work closely with marketing teams to independently evaluate campaign performance, ROI, and channel effectiveness, providing data‑driven recommendations that inform strategy and budget allocation. Ultimately, you’ll help the business gain an unbiased, evidence‑based view of how well marketing performs and where future investment should be made. The candidate. * Advanced analytical and statistical capability, with proven experience in marketing attribution modelling, campaign performance analysis, and ROI measurement. * Expertise in multi‑touch attribution, MMM - marketing mix modelling, experimental design, and incrementality testing, with the ability to apply these methodologies in real‑world marketing contexts. * Channel‑level marketing experience across paid search (PPC), paid social, and programmatic. * Ability to translate complex data insights into clear, actionable business recommendations, tailoring outputs for both technical and non‑technical audiences. * Excellent stakeholder management and communication skills, with experience consulting and influencing senior leaders. * Deep understanding of digital marketing metrics, customer journey analytics, and performance measurement frameworks across channels and platforms. * Commercial mindset with a collaborative working style, able to partner effectively with marketing, finance, data, and technology teams to drive data‑informed decision‑making. nice to have… * Proficiency in Python and SQL to support modelling, data manipulation, and exploratory analysis. * Broader machine learning experience, such as uplift modelling, predictive modelling, clustering, or propensity modelling. * Experience in market research methodologies (quantitative or qualitative) to complement analytical insight with customer understanding. * Exposure to customer journey, behavioural analytics, profitability or LTV, helpful for linking marketing impact to downstream customer outcomes