Data Analytics Manager

Working at the RFU means being part of the ‘bigger picture’ at England Rugby: to be rooted in our purpose, which is to enrich lives, introduce more people to rugby union & develop the sport for future generations. If our purpose resonates with you, and you recognise the value that sport can bring to people’s lives, we’d love to work with you. An opportunity has arisen for a Data Analytics Manager to join our Marketing team on a permanent basis.

Job Title : Data Analytics Manager

Department : Marketing

Reports to : Senior Customer Data Analytics Manager

Salary : c.£47,000 per annum

Job Level : Guide

Location : This role is contractually based at Allianz Stadium, offering some flexibility to work from home

Employment Type : Permanent

Working Hours : This is a full-time role, covering 35hrs per week

Application Information:

• Please submit an anonymised CV (i.e. remove personal details). You do not need to submit a cover letter
• Vacancy closing date: Sunday 26th April at 9pm.

To help us get to know your unique experience and voice, we kindly ask that you complete your application without the use of AI‑generated content. This ensures we can fairly and accurately understand your skills, perspective, and suitability for the role.

The Role:

The RFU is delivering an ambitious strategic plan to become a data-driven, user-centric organisation with market-leading digital and analytics capabilities. This transformation will reshape the rugby experience for players, volunteers and fans today while future-proofing the governing body for years to come.

As a Data & Analytics Manager within the Advanced Data Analytics team, you will be a driving force behind the RFU’s customer analytics capability. You will design, build and operationalise a suite of analytical models including fan, player and volunteer segmentation, growth models, customer lifetime value (CLV), propensity models and price elasticity analysis etc. These assets will directly inform commercial, marketing and engagement strategy across England Rugby.

This is a highly visible, hands-on role that blends advanced data science with compelling storytelling. You will be expected to translate complex analytical outputs into clear, actionable recommendations and present them with confidence to senior stakeholders, commercial partners and cross-functional teams. The ability to present work clearly, persuasively and at the right level of detail is as critical as technical excellence.

You will work primarily in Python for model development and data science workflows, leverage AWS services (Glue, ECS, SageMaker) for scalable data analytics and model deployment, and use Tableau to build dashboards and reporting layers that make analytical outputs accessible to the wider business. Collaboration and documentation are central to the role, using GitHub for version control and Confluence for knowledge sharing and Jira for project management.

Some key responsibilities include:

Customer Analytics Suite

• Support the design, build and continuous improvement of the RFU’s customer analytics models, including fan segmentation (RFM, behavioural clustering), player and volunteer segmentation, growth/propensity models, CLV estimation and price elasticity analysis.
• Support the Development and maintenance of production-grade Python pipelines that power the analytics suite, ensuring models are reproducible, version-controlled (GitHub) and well-documented (Confluence).
• Deploy and monitor models at scale using AWS infrastructure - Glue for ETL, ECS for containerised workloads, and SageMaker for model training and serving.
• Continuously validate and refine models against business outcomes, iterating on feature engineering, methodology and data sources to improve accuracy and commercial impact.

Insight, Storytelling & Presentation

• Present analytical findings to senior leadership, commercial teams and external partners with clarity and confidence, translating complex models into business narratives that drive decisions.
• Build and maintain Tableau dashboards that surface segmentation outputs, CLV scores, propensity flags and campaign performance metrics to non-technical stakeholders.
• Create compelling presentations and written briefings (decks, one-pagers, reports) that communicate the “so what” behind the data, not just the numbers.
• Champion a data-driven culture across the RFU by making analytics accessible, running insight sessions and proactively surfacing opportunities.

Stakeholder Collaboration & Strategy

• Partner with Marketing, Commercial, Digital Product and Insights teams to align analytics priorities with strategic objectives and campaign planning cycles.
• Shape the customer analytics roadmap in collaboration with the Advanced Data Analytics team, identifying new model opportunities and data enrichment strategies.
• Challenge existing assumptions with evidence-based analysis, influencing strategy through data rather than intuition.
• Support campaign