Summary
As a key part of our Quality & Inventory team, you will be responsible for reporting and analysing data and driving quality and inventory improvements throughout the organisation. In this development role, you will work closely with all areas of the organisation whilst working through your Apprenticeship study and learning all aspects of the role.
Wage
£23,000 a year
Training course
Data analyst (level 4)
Hours
Monday to Friday
40 hours a week
Start date
Sunday 1 June 2025
Duration
2 years
Positions available
1
Work
Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.
What you’ll do at work
As a Data Analyst Apprentice, your role will support the Quality and Inventory team and will have responsibility for the following:
* Identify data sources to meet the organisation's requirement, using evidence-based decision making to establish a rationale for inclusion and exclusion of various data sets and models
* Liaise with the client and/or colleagues from other areas of the organisation to establish reporting needs and deliver accurate information
* Collect, compile and, if needed, cleanse data, such as sales figures, solving any problems that arise, to/from a range of internal and external systems.
* Produce performance dashboards and reports
* Support the team on day-to-day tasks and reporting
* Collect, analyse and document business functionality and data requirements
* Collaborate with end users and project team members on required development and design
Where you’ll work
EMR Liverpool Alexandra Dock
Alexandra Building
Liverpool
L20 1BX
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
College or training organisation
APPRENTIFY LIMITED
Your training course
Data analyst (level 4)
Equal to higher national certificate (HNC)
Course contents
* Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
* implement the stages of the data analysis lifecycle
* apply principles of data classification within data analysis activity
* analyse data sets taking account of different data structures and database designs
* assess the impact on user experience and domain context on data analysis activity
* identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
* undertake customer requirements analysis and implement findings in data analytics planning and outputs
* identify data sources and the risks and challenges to combination within data analysis activity
* apply organizational architecture requirements to data analysis activities
* apply statistical methodologies to data analysis tasks
* apply predictive analytics in the collation and use of data
* collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
* use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
* collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
* select and apply the most appropriate data tools to achieve the optimum outcome
* Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
* implement the stages of the data analysis lifecycle
* apply principles of data classification within data analysis activity
* analyse data sets taking account of different data structures and database designs
* assess the impact on user experience and domain context on data analysis activity
* identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
* undertake customer requirements analysis and implement findings in data analytics planning and outputs
* identify data sources and the risks and challenges to combination within data analysis activity
* apply organizational architecture requirements to data analysis activities
* apply statistical methodologies to data analysis tasks
* apply predictive analytics in the collation and use of data
* collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
* use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
* collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
* select and apply the most appropriate data tools to achieve the optimum outcome
Your training plan
Level 4 Data analyst apprenticeship standard, including Functional Skills in English and maths if required.
Requirements
Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.
Skills
* Attention to detail
* Organisation skills
* Customer care skills
* Problem solving skills
* Administrative skills
* Number skills
* Team working
* Initiative