At a Glance
- Tasks: Lead a team to transform data into actionable insights and drive business performance.
- Company: Join Marks & Spencer, a forward-thinking retail leader committed to innovation.
- Benefits: Enjoy a 20% discount, competitive holidays, and tailored training from day one.
- Other info: Inclusive culture with opportunities for personal growth and community support.
- Why this job: Be at the forefront of analytics, shaping the future of retail with your expertise.
- Qualifications: Experience in leading analytics teams and strong skills in SQL, Python or R required.
The predicted salary is between 56700 - 69300 £ per year.
Are You Ready to Lead a team to turn data into competitive advantage and help shape the future of analytics at our Castle Donington Distribution Centre? Join a team based on site as the Lead Data Analytics Manager and be at the forefront of our data-driven transformation, where advanced analytics play a critical role in driving commercial performance, operational efficiency, and strategic decision-making. This is an opportunity to lead a team of talented analysts, delivering predictive models, experimentation, and analytical solutions that solve complex business challenges and generate measurable value.
Working across Data Science, Data Product, Engineering, and business teams, this role translates commercial priorities into impactful analytical outcomes, influencing decisions through robust insight, innovation, and scalable analytics capabilities. As a key leader within the broader Data & AI function, the role will champion best practice, foster a culture of experimentation and continuous learning, and help accelerate the organisation's analytical maturity.
The ideal candidate will bring proven experience leading high-performing analytics teams, combined with a strong retail or FMCG background and expertise in advanced analytics, statistical modelling, forecasting, and experimentation. Strong technical skills in SQL and tools such as Python or R will be complemented by a track record of delivering analytical solutions that drive measurable business impact. The ability to collaborate across data, product, engineering, and business teams, while translating complex data into clear commercial insights, will be key to success in this role.
NB this role is based at our Distribution centre in Derbyshire but regular travel to our London Support centre will be required.
Your key accountabilities will include:
- Lead the analytics agenda for highly automated distribution centres and end-to-end logistics operations, using data from warehouse management, warehouse control, automation, transport and labour systems to monitor performance, identify constraints and improve flow, capacity, service, productivity, cost and resilience.
- Drive advanced analytics solutions by applying statistical modelling, predictive analytics, forecasting, optimisation, and experimentation to solve complex business challenges and unlock commercial value.
- Partner with operations, engineering, automation vendors and technology teams to define measures, diagnose system and process issues, evaluate changes and ensure insight supports safe, stable and effective operation of robotics, material-handling equipment and other automation technologies.
- Shape and deliver the advanced analytics roadmap, prioritising initiatives that enhance decision-making, improve operational performance, and support organisational growth.
- Act as a trusted analytics leader, championing best practices, promoting a test-and-learn culture, and communicating complex insights through compelling data storytelling and visualisation.
Your skills and experience will include:
- Proven experience leading and developing high-performing analytics teams, creating an environment that fosters innovation, collaboration, and continuous improvement.
- Strong retail or FMCG expertise, with a deep understanding of commercial and operational drivers and the ability to apply analytics across areas such as material flow planning, labour scheduling, supply chain optimisation, and forecasting.
- Advanced analytical and technical capability, including statistical modelling, experimentation, forecasting, predictive analytics, and proficiency in SQL and tools such as Python or R to work with large, complex datasets.
- Track record of delivering high-impact analytics solutions, leading projects from problem definition through to stakeholder adoption and measurable business outcomes.
- Exceptional stakeholder management and communication skills, with experience working across cross-functional teams and translating complex analytical findings into clear, actionable commercial insights.
Working at M&S means being part of something bigger - helping to deliver quality, value and service to millions of customers every day. We're inclusive, fast-moving and always evolving, with a strong sense of purpose and a focus on doing the right thing. Here are just a few of the benefits that make working here even more rewarding:
- 20% colleague discount on all M&S products and many third-party brands for you and someone in your household, available once you've completed your probation.
- Competitive holiday allowance with the option to buy more.
- Discretionary bonus schemes linked to your performance and ours.
- Strong pension and life assurance to help plan for the future.
- Tailored induction and training to support your development from day one.
- Exclusive perks and savings through our M&S Choices portal.
- Market-leading family policies, including parental, adoption and neonatal leave.
- 24/7 wellbeing support, including virtual GP access and mental health services.
- One paid volunteer day a year to support a cause that matters to you.
We are ambitious about the future of retail. We're reinventing, innovating and leading the industry into a more conscientious, inspiring digital era. We're redefining how we work together and offering our most exciting opportunities yet. Marks & Spencer strives to be an inclusive organisation, trusted and admired by our colleagues, customers and suppliers. Join us and make change happen. We are committed to building diverse and representative teams, where everyone can bring their whole selves to work and be at their best. We support each other and work together to win together. If you feel you'd benefit from any support or reasonable adjustments during any stage of the recruitment process, please don't hesitate to let us know when completing your application.
Analytics Manager - Distribution employer: Marks and Spencer
Marks and Spencer is an exceptional employer that fosters a culture of innovation and collaboration, particularly within the Corporate HR technology team. Employees benefit from a supportive environment that prioritises professional growth and development, alongside competitive remuneration and benefits. Working in a dynamic location, you will have the opportunity to lead impactful projects that enhance the colleague experience throughout their journey with the company.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Manager - Distribution
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We think you need these skills to ace Analytics Manager - Distribution
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 Marks and Spencer. 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!
How to prepare for a job interview at Marks and Spencer
✨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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✨Get Comfortable with Python and R
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