Commercial Data Analyst

Halfords
Redditch
1 year ago
Applications closed

Related Jobs

View all jobs

Junior Data Scientist / Data Analyst

Product Data Scientist

Principal Data Scientist

Actuarial Data Scientist

Senior Pricing Data Scientist

Senior Data Scientist

About us

At Halfords, our mission is to inspire and support a lifetime of motoring and cycling. As a specialist retailer, we lead the market through customer-driven innovation and a distinct product range. We are dedicated to providing our customers with an integrated, unique, and convenient service experience—from e-bike and electric vehicle servicing to on-demand solutions. Our commitment is to foster customer loyalty by offering compelling reasons to keep coming back to our stores, ensuring a lifetime of motoring and cycling enjoyment.

The teams at our Redditch Support Centre work with every other area of our business, putting them at the heart of the action and playing a key role in our success and growth. Everyone brings their individual knowledge and experience to work every day, working as one team to keep things moving smoothly.

If you’re willing to  get stuck in, you’ll love it here too. So put yourself at the heart of a dynamic, fast-paced working environment where expertise and focus take people far.

 

About the role

As a Commercial Data Analyst, you'll analyse complex datasets to drive business improvements, optimise efficiency and improve customer experience. Collaborating with the Quality, Returns, and ESG teams, you'll maintain reports and data workflows in Power BI, using advanced SQL, DAX, and Excel skills. You’ll also automate processes and deliver insights aligned with business goals.

 

Key Accountabilities

  • Data and Reporting Ownership:Manage and deliver precise and timely reports for the Quality Team, ESG, and Commercial Returns. These insights drive improvements in product performance, customer satisfaction, compliance, and commercial returns agreements, directly influencing business decisions and success.
  • Report Production & Maintenance:Develop and sustain a schedule of quarterly, monthly and weekly reports, including dashboards and regular updates.
  • Enhancements and Implementation:In-line with company data reporting policies and the move to Group Data Platform. Recommend, design, and implement enhanced reporting solutions and system improvements. E.g. automation.
  • Ad Hoc Projects:Undertake any ad hoc projects or tasks within the scope of the Product Quality analysis or improvement. E.g. Better Buying Programme, Cost of Goods, etc
  • Commitment to Continuous Improvement: Exhibit a dedication to innovation and continuous improvement in data analytics and business ethics.
  • Training and Mentorship:Participate actively in training and mentorship programs to expand skills and knowledge.

 

Skills and Experience

  • At least BSc graduate in Data Science or Analytics, or similar.
  • Up to 5 years in a similar role in a commercial environment.
  • Highly Proficient in Spark SQL, Azure Databricks, Excel, MS Office 365, and Power BI.
  • Knowledge of SAP BW, Alteryx.
  • Practical experience in extracting, cleaning, and reporting data.
  • Keen ability to identify discrepancies in large data sets.
  • Exceptional attention to detail, capable of producing accurate work under tight deadlines.
  • Ability to connect ideas and do things differently.
  • Strong teamwork and collaboration skills.

Not sure you meet all the criteria? We'd encourage you to take the wheel and apply anyway! At Halfords we are committed to creating an inclusive workplace for our colleagues. We're an equal opportunities employer and proud to welcome applications from all backgrounds and embrace diversity within our one Halfords Family.

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.