EMEA Marketing Measurement Lead
London, UK (Unknown)
Posted 5 weeks ago
Job Summary
Own the measurement strategy and delivery for Google's EMEA marketing, leading advanced measurement, modeling, and analytics to guide media planning, budget allocation, and impact assessment.
- Lead measurement roadmap and data frameworks for EMEA
- Manage and develop a high-performing team of analysts and data scientists
- Partner with cross-functional leaders to drive business decisions
Job Description
Responsibilities
- As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
- As the EMEA Marketing Measurement Lead, based in London, you will lead the measurement team responsible for evaluating and optimizing Google's marketing investments across Europe, the Middle East, and Africa (EMEA). Acting as an advertiser, Google Marketing runs full-funnel campaigns to build brand equity and drive performance across critical product areas, including hardware and core consumer services.
- In this pivotal role, you will lead and deliver advanced measurement, implement analytical models, develop key metrics, and build statistical frameworks to measure marketing incrementality, media effectiveness, and overall business impact. You will act as a key strategic partner to EMEA Marketing Leadership, Finance, and Product Area teams, bridging analytical mastery with business strategy to guide media planning and allocation to drive impact and growth
- Drive the development of measurement roadmap to solve complex data questions for EMEA campaigns. Define data requirements, analytical frameworks, and regional strategy to scale media measurement efforts.
- Set and achieve ambitious measurement goals aligned with global marketing objectives. Drive AI transformation to enhance productivity, analytical creativity, and innovation, while upholding Google's AI Principles.
- Oversee the analysis and interpretation of high-dimensional datasets to deliver actionable results. Act as a domain expert to review statistical analyses, methodologies.
- Partner with cross-functional leadership (including Media CoE, Finance, Product Areas) to guide marketing budget allocation, answer complex statistical questions, and ensure decision-making is aligned with objectives.
- Manage and coach a high-performing team of Business Data Scientists and Analysts. Advocate knowledge sharing, collaboration, and solution reuse across Google’s broader marketing analytics and data science communities.
Requirements
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
- 3 years of experience in people management, in leading, mentoring, and developing technical and analytical teams.
- Experience writing, reviewing, and maintaining code for data manipulation and analysis using programming languages (such as Python, R, SQL).
- Experience presenting to non-technical audiences.
Preferred
- PhD in a quantitative fields such as Statistics, Mathematics, Economics, Operations Research, Data Science.
- Experience in advanced marketing measurement methodologies (e.g., conversion lift, geo-experiments, Media Mix Modeling, brand lift studies) for a major regional or global brand.
- Experience collaborating cross-team to define data requirements, analyze product metrics, resolve data gaps.
- Knowledge of statistics (e.g., causal inference, predictive modeling, survey methodology) to solve multi-dimensional, complex business problems.
- Excellent communication, executive-influence skills, with an ability to translate complex quantitative findings into actionable insights for senior leaders.
- Proficiency managing large, complex datasets.
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