Data Analyst

  • Full Time
  • Tamworth
  • Salary Guide: £25,000 - £40,000


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Euro Car Parts Ltd

We are a people first organisation for our colleagues, the customer is at the heart of everything we do, and in turn we put our colleagues at the fore... Role: Data Analyst, Category: IT & Telecoms, Size: 11-50

Data Analyst: Euro Car Parts Ltd

We are a people first organisation for our colleagues, the customer is at the heart of everything we do, and in turn we put our colleagues at the forefront of our business. As with many of our roles, we are happy to talk about flexible working options, we are committed to supporting a healthy work-life balance. Were looking for people who love what they do, are passionate about delivering only the very best and make it their business to excel, whatever their role. We strive to support all our employees through their individual career paths and thrive within our business.

Position: Data Analyst
Location: Tamworth
Hours: Full Time
Salary Guide: £25,000 – £40,000
Last Updated: 03 August 2022
Job Category: IT & Telecoms

Data Analyst Role:

A Data Analyst, or a Digital Data Analyst, collects and analyses data to identify trends and provide clients or management with valuable information that they can use to improve marketing, operational and businesses practices. Main duties include identifying, gathering, analysing data and making their insights accessible to the company through easy-to-understand graphs, charts, tables and reports.

Other Duties:

  • Using data mining to extract information from data sets and identify correlations and patterns 
  • Organising and transforming information into comprehensible structures
  • Using data to predict trends in the customer base and the consumer population as a whole
  • Performing statistical analysis of data
  • Using tools and techniques to visualise data in easy-to-understand formats, such as diagrams and graphs
  • Preparing reports and presenting these to management or clients
  • Identifying and recommending new ways to save money by streamlining business processes
  • Monitoring data quality and removing corrupt data
  • Communicating with stakeholders to understand data content and business requirements



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