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.