# VP Statistical Measurement at WPP

WPP is hiring a VP Statistical Measurement in London, United Kingdom. Level rates it Works on AI ●●●○; you can [apply on Level](https://jobsbylevel.com/go/41bd0c99-f3dc-42db-b1c9-0a3d43646ee9?utm_medium=ai-agent).

AI Level 3, AI centrality 65 out of 100. London, England, United Kingdom.

## Details

- Company: [WPP](https://jobsbylevel.com/companies/wpp)
- AI level: AI Level 3 (score 65 out of 100)
- Location: London, England, United Kingdom
- Posted: October 15, 2026
- Apply: https://jobsbylevel.com/go/41bd0c99-f3dc-42db-b1c9-0a3d43646ee9?utm_medium=ai-agent

## Prepare for this job

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## Description

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. About the role We’re looking for a VP, Statistical Measurement to lead statistical methodology, measurement standards and quantitative quality across our Open Intelligence Solutions (OIS) portfolio. This is a senior leadership role within Strategic Data Science, focused on ensuring that the analytical work we produce is rigorous, credible and commercially meaningful . You’ll be the organisation’s authority on statistical methodology and numerical quality, helping teams turn complex data into robust evidence that clients and senior stakeholders can trust. You’ll shape the evolution of Marketing Mix Modelling (MMM), attribution, incrementality, causal inference and experimental design , while establishing consistent standards for validation, statistical quality assurance and communicating uncertainty. You’ll also play an important role in preparing the organisation for an increasingly AI-assisted analytical environment , ensuring that both people and AI-enabled workflows apply statistical methods responsibly and communicate findings accurately. What you’ll do Own statistical methodology and measurement standards Own statistical methodology and measurement standards across the OIS portfolio. Ensure analytical approaches are technically rigorous, fit for purpose and consistently applied. Establish standards for statistical hygiene, validation, uncertainty and quantitative quality assurance. Ensure analytical claims are supported by robust experimental, causal and econometric evidence. Act as the organisation’s authority on numerical quality, measurement credibility and analytical validity. Challenge weak assumptions, over-claims and methodological risks before outputs reach senior stakeholders or clients. Shape the future of measurement Lead the evolution of MMM and econometric measurement capabilities , ensuring approaches are robust, interpretable and aligned to commercial decision-making. Develop frameworks and practical guidance for attribution, causal inference, experimental design and incrementality . Create validation frameworks and QA mechanisms that increase confidence in measurement outputs. Establish best practices around model diagnostics, sensitivity testing and evidence thresholds. Partner directly with clients and senior stakeholders to ensure measurement outputs are credible, understandable and commercially actionable. Build statistical capability across the organisation Develop tools, frameworks and approaches that improve statistical storytelling, insight communication and data visualisation. Lead and develop Senior Measurement Scientists and Statistical Specialists across areas including econometrics, MMM, experimental design, incrementality, attribution, causal inference, statistical QA and validation. Build statistical education and capability programmes that raise the standard of analytical thinking across the organisation. Help develop responsible AI-assisted analytical workflows , ensuring statistical methods are applied appropriately and outputs are communicated clearly. Work closely with OIS R&D, Product, Enterprise Technology, Data Platform, DTS Product & Engineering, WPP Open,

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