At a Glance
- Tasks: Lead high-impact analytics projects to drive strategic decisions and commercial performance.
- Company: Dunelm, the UK's top choice for homewares, fostering a welcoming workplace.
- Benefits: Flexible hybrid work model, competitive salary, and opportunities for personal growth.
- Other info: Join a dynamic team focused on innovation and collaboration in a thriving environment.
- Why this job: Make a real impact in a £2bn omnichannel retail business with your analytical expertise.
- Qualifications: Significant experience in leading analytics teams and delivering measurable value.
The predicted salary is between 75600 - 92400 £ per year.
This role can be based out of our Leicester or London office.
Home. There’s no place like it.
And there’s no feeling like helping people create the joy of feeling truly at home.
At Dunelm, that’s what we do.
We’re the UK's number one choice for homewares because we make home life lovelier for our customers.
And we’ve crafted a workplace that feels just as welcoming – where you can bring your ideas, be yourself, and feel right at home .
Work your way, together
We’re a hybrid business, which means you’ll have flexibility alongside time together with your team.
In this role, you can expect min 3 days per week in the office or on-site, helping you stay connected, collaborate and do your best work for our customers.
Role Purpose
We are looking for a Head of Analytics to lead the team responsible for delivering high-impact analytics projects across a £2bn omnichannel retail business.
This role will be accountable for ensuring that analytics drives better decision making, commercial performance and strategic outcomes across the organisation.
They will ensure that the function is focused on the highest-value opportunities, that projects are prioritised effectively and that analytics is translated into clear recommendations and measurable business action.
It will be responsible for creating the operating model, governance and ways of working that enable analytics teams to consistently deliver impact.
Key Responsibilities
- Define the Analytics Strategy and Portfolio
- Define the strategy, priorities and roadmap for analytics across the business
- Translate the broader business and data strategy into a clear pipeline of analytics activity
- Balance short-term business priorities with longer-term strategic and capability-building projects
- Ensure every project has a clear business problem, success measures and identified commercial value
- Lead Delivery of High-Impact Analytics Projects
- Oversee the delivery of a portfolio of analytics projects across customer, digital, marketing, stores, supply chain and commercial
- Ensure projects deliver robust insight, clear recommendations and measurable business outcomes
- Support teams to tackle complex business questions
- Ensure that analytics is used not just to explain performance, but to influence decisions and actions
- Stakeholder Leadership
- Build strong relationships with directors and senior stakeholders across the organisation
- Help leaders frame business problems, define priorities and identify where analytics can add the most value
- Influence strategic decisions using evidence, insight and structured analysis
- Challenge assumptions and ensure business decisions are based on robust data rather than intuition alone
- Lead and Develop the Team
- Build a high-performing team with strong commercial understanding, analytical capability and stakeholder management skills
- Ensure the team has the right mix of expertise across customer, digital, marketing, commercial and operational analytics
- Develop future leaders and create clear development and succession plans
- Set high standards for analytical quality, pace, impact and storytelling
- Improve the Analytics Operating Model
- Define and embed a consistent approach to how projects are scoped, prioritised, delivered and measured
- Introduce stronger project governance, value tracking and stakeholder engagement processes
- Ensure teams work effectively with business intelligence, data science and engineering teams
- Improve how analytics is embedded into planning cycles, trading reviews, investment decisions and business performance management
- Drive more repeatable and scalable ways of working across the analytics function
- Work in Partnership with Data Science and Engineering
- Work closely Data Science to identify where predictive models, forecasting and advanced analytics can support business decisions
- Partner with data engineering teams to ensure Analytics has access to the right data, tools and models
- Influence priorities for new datasets, data products and analytical capabilities
- Ensure that analytics projects are built on strong, trusted and scalable data foundations
Skills and Experience Required
- Significant experience leading analytics teams within retail, ecommerce or another customer-facing business
- Proven track record of leading a portfolio of analytics projects that delivered measurable value
- Strong understanding of omnichannel retail and the key drivers of performance across stores and digital
- Experience influencing senior stakeholders and shaping major business decisions
- Experience leading and developing high-performing analytical teams
- Strong commercial acumen and ability to connect analytics to business value
- Strong understanding of a broad range of analytical techniques
- Experience defining analytics operating models, governance and project prioritisation
- Strong communication, storytelling and stakeholder management skills
- Strong analytical capability, with experience using SQL and analytical tools such as Python or R
- Experience with experimentation, forecasting, predictive analytics or optimisation
- Experience working with business intelligence, data science and engineering teams
- Experience within a large-scale omnichannel retailer
- Key Behaviours
- Strategic and commercially minded
- Strong and inspiring people leader
- Highly credible with senior stakeholders
- Comfortable operating in ambiguity and solving complex problems
- Strong communicator and storyteller
- Collaborative and able to build partnerships across the business
- Passionate about improving how the organisation uses data to make decisions
- #J-18808-Ljbffr
Head of Analytics in Leicester employer: Dunelm
As a Visual Merchandiser with us, you'll thrive in a dynamic and supportive work environment that values creativity and teamwork. We offer competitive pay, flexible scheduling, and opportunities for professional growth, ensuring you can develop your skills while contributing to an inspiring shopping experience for our customers. Join us in a location that prioritises a customer-first approach, where your attention to detail will shine and make a real impact on store performance.
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We think this is how you could land Head of Analytics in Leicester
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We think you need these skills to ace Head of Analytics in Leicester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Dunelm. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
