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.

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 effectiveness measurement by providing audience segmentation, targeting recommendations and post-campaign attribution analysis.
• Support digital analytics initiatives where they intersect with customer analytics, including analysis of web behaviour, campaign performance and digital engagement metrics.
• Contribute to personalisation efforts in collaboration with the Digital Product team, including A/B test design and evaluation where relevant to segmentation and targeting.

Data Analytics Platform

• Design and maintain ETL pipelines in AWS Glue that prepare, enrich and transform data from CRM, ticketing, digital and third-party sources for downstream modelling.
• Ensure data quality and integrity across the analytics pipeline, implementing validation checks and monitoring for drift or degradation.
• Support digital analytics initiatives where they intersect with customer analytics, including analysis of web behaviour, campaign performance and digital engagement metrics.

Leadership & Continuous Improvement

• Mentor and upskill team members in Python, statistical methods and analytics best practices.
• Propose and implement process improvements that enhance the efficiency, reproducibility and impact of analytical work across the team.
• Act as an ambassador for the RFU, promoting its core values and contributing to its mission of becoming a leader in data-driven sport.
• Undertake other duties as needed to support the evolving needs of the organisation.

Qualifications, Skills & Experience:

The skills and attributes outlined in this description are not exhaustive and we welcome candidates who can bring different relevant experiences to the role.

Essential:

• Demonstrable experience in a data science or advanced analytics role, with a strong track record of building and deploying analytical models (segmentation, propensity, CLV or similar).
• Strong Python proficiency for data science - pandas, scikit-learn, NumPy, and experience with production-quality code (not just notebooks). SQL is also a must for this role.
• Experience with AWS cloud services, ideally including Glue (ETL), ECS (containerised workloads) and SageMaker (model training/deployment).
• Excellent presentation and communication skills - proven ability to distil complex analytical concepts into clear, compelling narratives for senior and non-technical audiences. This is non-negotiable.
• Proficiency with Tableau (or equivalent BI tool) for building dashboards and data visualisations that drive business decisions.
• Experience with GitHub for version control and collaborative development, and Confluence (or similar) for documentation and knowledge sharing.

Desirable:

• Background in sport, entertainment or a membership/subscription business.
• Experience with a Customer Data Platform.
• Bachelor’s degree in a relevant field (e.g., Data Science, Business Analytics, Maths, Sciences).
• Experience with Python and Machine Learning.
• Experience with Docker, CI/CD pipelines or MLOps practices.
• Familiarity with Google Analytics 4, Google Tag Manager or web analytics tooling.

Additional Information:

• We want you to have every opportunity to demonstrate your skills, ability and potential. If there is anything we could do to support you through your application or to provide the best environment for your interviews, including assistance or adjustment, please reach out to recruitment.
• During your application, we will ask questions about your identity. This information is considered highly confidential and will not be seen by hiring managers. You can find out more about why we ask these questions here.