Summary
Imagine what’s next. Imagine playing a key role in building a data-driven future to Help Britain Prosper. Make it real. Apply now for our Data Analyst apprenticeship programme.
Wage
£25,000 a year
You will join us on a fixed apprenticeship salary where you’ll be eligible for annual pay reviews. Upon successful completion of the apprenticeship, your salary will be increased in line with the grade and pay range for your role.
Training course
Data analyst (level 4)
Hours
Monday to Friday. Shifts tbc.
35 hours a week
Possible start date
Monday 1 September
Duration
1 year 6 months
Positions available
12
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
Your apprenticeship will take around 18 months to complete and will cover key areas such as:
* Analytics lifecycles
* Data democratisation
* SQL data extraction
* Advanced data joins
* Advanced visualisation of data
* Statistical programming languages
* Predictive modelling and forecasting
* Statistics in analysis
* Creating and delivering a great data product
Where you’ll work
Bristol
BS1 5LF
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
FIREBRAND TRAINING 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
Training schedule has yet to be agreed. Details will be made available at a later date.
More training information
* L4 Data analyst Apprenticeship Standard
Requirements
Essential qualifications
GCSE in:
* English (grade 4-9)
* Maths (grade 4-9)
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
* Problem solving skills
* Team working
* Creative
* Aiming high
* Staying positive