Summary
Please see here for more information and details on how to apply:
Wage
£23,000 a year
Training course
Data analyst (level 4)
Hours
Monday to Friday, 9am to 5pm. 1 day a week will be dedicated to apprenticeship learning.
35 hours a week
Possible start date
Monday 22 September
Duration
2 years
Positions available
3
Work
As an apprentice, you’ll work at a company and get hands-on experience. You’ll gain new skills and work alongside experienced staff.
What you’ll do at work
* The apprenticeship rotation programme will provide a hands-on experience of the end-to-end asset management process
* You’ll see first-hand how money moves through the business, how investments are analysed and how we ensure the process is optimised to keep things running smoothly.
* Develop your skills and knowledge within a fast-paced and progressive environment.
Where you’ll work
Windsor House
Ironmasters Way, Town Centre
Telford
TF3 4NB
Training
An apprenticeship includes regular training with a college or other training organisation. At least 20% of your working hours will be spent training or studying.
College or training organisation
BPP UNIVERSITY 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
* L4 Data analyst Apprenticeship Standard
Requirements
Essential qualifications
GCSE in:
* in at least 5 subjects (grade 9-4)
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
* Communication skills
* Attention to detail
* Organisation skills
* Problem solving skills
* Administrative skills
* Team working