Head of Performance & Analytics
Role details
Job location
Tech stack
Job description
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Own the cross-channel measurement framework across PPC, SEO, Content and Outreach
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Define and maintain a single source of truth for performance reporting
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Lead attribution modelling and performance interpretation (accepting real-world limitations)
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Translate complex data into clear, actionable insight for channel leads and clients
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Design and deploy AI-driven models and automations to:
o Identify high-performing audiences, creatives, keywords and content themes o Predict performance trends, saturation points and diminishing returns o Improve budget allocation and prioritisation across channels
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Integrate AI tooling with advertising platforms, analytics stacks and internal systems
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Evaluate emerging AI technologies and apply them pragmatically (not experimentally)
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Own the agency-wide experimentation roadmap
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Design structured tests with clear hypotheses, success criteria and learning outcomes
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Introduce advanced testing methodologies (e.g. multi-armed bandits, automation-led testing)
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Ensure learnings are embedded back into channel strategies, not left as theory
Cross-Channel Enablement & Influence
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Act as a strategic partner to PPC, SEO, Content and Outreach team members
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Create performance feedback loops between channels
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Challenge assumptions and surface opportunities teams may miss
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Provide clear recommendations that channel leads are expected to action or challenge with evidence
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Support senior client conversations with insight, forecasting and performance rationale
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Help clients understand why performance is moving, not just what happened
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Drive measurable improvements in blended CPA, ROAS, efficiency and scalability
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Ensure AI and automation directly support commercial outcomes, not vanity metrics
Requirements
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Strong background in performance marketing analytics, data science, or growth analytics
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Proven experience working across multiple channels (PPC, SEO, content, digital PR)
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Advanced skills in data analysis and modelling (Python, SQL essential)
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Experience with GA4, BigQuery, Looker (or similar BI tools)
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Understanding of ad platform mechanics and APIs (Google, Meta, etc.)
- Commercial mindset - able to balance statistical rigour with business reality
Desirable
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Experience implementing AI or ML models in marketing environments
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Familiarity with automation tools, cloud data platforms, and LLMs for analysis
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Agency experience or working in fast-paced, client-facing environments
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Experience designing experimentation frameworks or predictive models