Quality & Inventory Data Analyst Apprentice

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

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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

About this company

European Metal Recycling is a global leader in sustainable materials with physical operations in the UK, USA, Germany and the Netherlands. Our core business is the recycling of metal and plastics from a range of public, commercial and industrial waste streams. Our recycling activities generate around 10 million tonnes of sustainable materials every year, saving over 10 million tonnes of CO2. Our mission is to have great people serving our customers with dependable recycling solutions. EMR is still privately owned, with family values at its core. It’s a place where we care about our people, our customers, our workplace and our communities. We offer diverse and exciting career opportunities where individuals can make a difference and are recognised and rewarded for their hard work.

After this apprenticeship

This role offers a rewarding career for the right candidate, but it also has a clear path for progression and development, which means a bright future awaits.

Ask a question

The contact for this apprenticeship is:

APPRENTIFY LIMITED

The reference code for this apprenticeship is VAC1000310277.

Apply now

Closes in 18 days (Tuesday 22 April 2025)

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