Senior Analytics Manager

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Why we're hiring:

The WPP DTS Business Intelligence team is looking for an exceptional Senior Analytics Manager to lead two of the four working pillars within our 14-person (and growing) global BI function: Product & Engineering Intelligence and Sentiment & Value Intelligence .

In this role, you will be the vital bridge connecting day-to-day tactical analytics with the broader WPP DTS Business Intelligence vision . You will partner directly with product leadership, engineering, UI/UX research, client, and market enablement teams to establish trusted telemetry, evaluate feature adoption, and measure the business value of our digital products.

You will have line management responsibility for 2 analysts (split across the UK and US), serving as a dedicated mentor and technical guide to help them deliver their best work and grow their careers. Working closely with the VP of Business Intelligence, you will establish unified tracking standards, integrate qualitative sentiment with behavioural data, and ensure our reporting delivers the critical 'so what' that inspires executive action.

This role is flexible hybrid.

What you'll be doing:

• Connect Tactical Delivery with Strategic Vision: Bridge day-to-day analytics execution with the overarching BI roadmap, ensuring that project-level deliverables advance wider organisational priorities.
• Project & Operational Leadership: Lead and manage multiple projects across the team, ensuring delivery remains on track with our roadmap, challenges are resolved or escalated efficiently, tasks are delegated effectively, and high standards of data quality and output integrity are maintained.
• Lead Product & Engineering Intelligence: Partner with product leadership, engineers, designers, and enablement teams to establish and maintain unified tracking and measurement standards, oversee the build of intuitive self-serve adoption dashboards, and deliver strategic deep dives that steer product roadmaps-adapting measurement and intelligence to the changing product landscape as required.
• Drive Sentiment & Value Intelligence: Partner with our colleagues in the Research team to make sense of product user sentiment and feedback. Synthesise behavioural product analytics with qualitative survey feedback into a cohesive narrative quantifying productivity, operational impact, and client outcomes.
• Team Mentorship & People Leadership: Line-manage, mentor, and coach 2 direct reports (UK and US), actively reviewing work, unblocking technical challenges, providing hands-on guidance, and fostering an environment of continuous learning and high analytical rigour.
• Champion Data Quality & Reconcile Complex Datasets: Take accountability for reporting accuracy and data integrity. Confidently reconcile messy, disparate, or fragmented data sources into structured, trustworthy reporting assets.
• Insight-Led Storytelling & Stakeholder Engagement: Act as a key business advisor across all levels of the organisation-engaging technical and non-technical stakeholders alike. Translate complex data into clear, compelling, and actionable stories that focus relentlessly on business impact rather than just numbers.
• Foundational Governance & Enablement: Collaborate with the wider BI team on our shared data infrastructure layer (BigQuery, Databricks) to uphold event taxonomy standards, KPI definitions, and governed data management.

What will you bring:

• Analytics Experience: Significant hands‑on experience in business intelligence, product analytics, data analytics, or equivalent roles, with a proven track record of moving beyond pure data 'reporting' to deliver actionable "so what" insights that influence decisions. Experience with Google Analytics or equivalent analytics packages would be particularly helpful.
• People Leadership & Mentoring: Demonstrated experience managing, coaching, or mentoring analysts; genuine enthusiasm for developing junior‑to‑mid‑level talent and guiding them through analytical and technical roadblocks.
• Navigating Messy & Fragmented Data: Proven ability to connect, clean, and reconcile diverse, non-standard datasets (e.g. behavioural event tracking, operationa

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