National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Group Supply Chain Data Scientist

Halfords
Worcestershire
11 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

AI & Data Scientist

Data Scientist

Lead Data Scientist...

Lead Data Scientist

Lead Data Scientist

Job Purpose

At Halfords we recognise our most important asset, after our people, is data, which is why we have invested in an Azure Databricks data lake. The challenge of course is to have skilled resource to unlock the valuable business insight within the data.

The Group Supply Chain Data Scientist is a new role and will work alongside the Group Supply Chain Analytics Manager. Both roles are responsible for analysing and interpreting large amounts of data from a range of internal and external sources, using algorithmic, data mining, artificial intelligence, machine learning and statistical tools, to make it available to Merchandise Planners and wider Supply Chain teams for decision making.

The Group Supply Chain Data Scientist will be responsible for the creation and maintenance of weekly KPI dashboards and actionable insight and use statistical and analytical methods plus AI tools to automate specific processes within Supply Chain and develop smart solutions to business challenges.

The role aims to ensure Halfords can leverage competitive advantage through the deployment of best-in-class analytics across planning and the end-to-end supply chain, driving continuous efficiency and effectiveness through automation and informed decision making, linking business strategy to insight.

Key Responsibilities

Work closely with the Supply Chain stakeholders to understand business goals and determine how data can be used to achieve these goals. Synthesize information from multiple internal and external sources to solve problems critical to the Supply Chain. Influence the ingestion of new data sources into the Group Data Platform, support the testing of new data and creation of Supply Chain measures for the business to use. Use machine learning tools and statistical techniques to produce solutions to problems and enable managers to make proactive decisions. Create clear dashboards and reports that provide compelling insight about our Group Supply Chain performance and highlight opportunities for improved customer service and business efficiencies. Interpret analytical results and clearly communicate findings, translating technical data insights into actionable strategies for non-technical stakeholders. Facilitate embedding a self-service capability for operational business users including automating as far as possible to reduce manual intervention and drive efficiency. Stay up to date with the latest Data Science technology, techniques and methods.

Key Skills/Experience

Proven experience as a Data Scientist or Data Analyst. Experience in data mining and data wrangling. Experience in open source big-data technologies and cloud (. Microsoft Azure). Experience of data warehouse and data lake structures . Azure Databricks, Snowflake as well as data visualisation tools . Microsoft Power BI, Tableau. Knowledge of statistical programming and database query languages . SQL, Python (including PySpark, a Python API for Spark, useful for Azure Databricks). R and Scala are an asset. Strong applied statistical and probability skills, including knowledge of statistical tests, distributions and regression. Understanding of machine-learning methods, like k-nearest neighbours, naive Bayes classifiers, support vector machines, random forests and an understanding of Operations Research. Strong problem-solving aptitude. Knowledge of retail Supply Chain and Merchandise Planning processes is an asset. Excellent communication and presentation skills demonstrating the ability to describe findings to a technical and non-technical audience. BSc/BA in computer science, mathematics, statistics, MORSE or relevant field; graduate degree in data science or another quantitative field is essential.

Personal characteristics

Analytical mind and business acumen. Highly numerate and high data handling capability. Ability to work accurately at pace. Attention to detail. Proactive, ‘can-do’ attitude with a solution-oriented approach. A continuous improvement mind-set. Constantly looking for ways to better things. Team player, with a collaborative style. Sense of humour. Personifies the Halfords values of ‘pride in expertise’, ‘wow our customers’, ‘be better every day’ and ‘one Halfords family’.
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide – we refresh it every quarter so you always know who’s really scaling their artificial‑intelligence teams. Artificial intelligence hiring has roared back in 2025. The UK’s boosted National AI Strategy funding, record‑breaking private investment (£18.1 billion so far) & a fresh wave of generative‑AI product launches mean employers are jockeying for data scientists, ML engineers, MLOps specialists, AI product managers, prompt engineers & applied researchers. Below are 50 organisations that have advertised UK‑based AI vacancies in the past eight weeks or formally announced growth plans. They’re grouped into five easy‑scan categories so you can jump straight to the kind of employer – & culture – that suits you. For each company you’ll find: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, culture, mission) Use the internal links to browse current vacancies on ArtificialIntelligenceJobs.co.uk – or set up a free job alert so fresh roles land in your inbox.

Return-to-Work Pathways: Relaunch Your AI Career with Returnships, Flexible & Hybrid Roles

Stepping back into the workplace after a career break can feel like embarking on a whole new journey—especially in a cutting-edge field such as artificial intelligence (AI). For parents and carers, the challenge isn’t just refreshing your technical know-how but also securing a role that respects your family commitments. Fortunately, the UK’s tech sector now boasts a wealth of return-to-work programmes—from formal returnships to flexible and hybrid opportunities. These pathways are designed to bridge the gap, equipping you with refreshed skills, confidence and a supportive network. In this comprehensive guide, you’ll discover how to: Understand the booming demand for AI talent in the UK Leverage transferable skills honed during your break Overcome common re-entry challenges Build your AI skillset with targeted training Tap into returnship and re-entry programmes Find flexible, hybrid and full-time AI roles that suit your lifestyle Balance professional growth with caring responsibilities Master applications, interviews and networking Whether you’re returning after maternity leave, eldercare duties or another life chapter, this article will equip you with practical steps, resources and insider tips.

LinkedIn Profile Checklist for AI Jobs: 10 Tweaks That Triple Recruiter Views

In today’s fiercely competitive AI job market, simply having a LinkedIn profile isn’t enough. Recruiters and hiring managers routinely scout for top talent in machine learning, data science, natural language processing, computer vision and beyond—sometimes before roles are even posted. With hundreds of applicants vying for each role, you need a profile that’s optimised for search, speaks directly to AI-specific skills, and showcases measurable impact. By following this step-by-step LinkedIn for AI jobs checklist, you’ll make ten strategic tweaks that can triple recruiter views and position you as a leading AI professional. Whether you’re a fresh graduate aiming for your first AI position or a seasoned expert targeting a senior role, these actionable changes will ensure your profile stands out in feeds, search results and recruiter queues. Let’s dive in.