Summary
Are you looking for a new opportunity to showcase your problem-solving and analytical skills? Do you have a passion for working with people and driving data to make decisions? To identify business problems and present insights in a compelling way that influences action? Our data apprenticeship is a fantastic opportunity to start your career in data
Annual wage
£22,500 a year
Pension – Thales match, plus 1%, with a maximum contribution of 7% Health Insurance – 50% of salary for five years Performance related pay uplifts
Training course
Data analyst (level 4)
Hours
Flexible working, Monday – Friday, 37 hours a week (8 hours Monday – Thursday, 5 hours Friday)
37 hours a week
Possible start date
Monday 1 September
Duration
1 year 6 months
Positions available
1
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
Within this role, you will be valued for your intellectual curiosity, innovative approach to problem-solving, and your strong analytical skills. You will be key in compiling data from multiple systems to tell stories and to answer vital business questions.
* Identify business problems and present insights to influence actions
* Develop skills in Data Engineering, Visualisation and Business Analysis in a complex business environment
* Work as part of a team to deliver data products used across the whole business
* Collaborate with business users to ensure you are delivering the insights they need
* Produce reports to provide insight and recommendations for how to improve the business operations, learning and business processes, and what drives business outcomes
Where you’ll work
Manor Royal
Crawley
RH10 9HA
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
DIGITAL NATIVE (UK) 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
You will be studying towards a Level 4 Data Analyst Apprenticeship delivered by Thales UK, in partnership with one of our specialist digital training providers. Delivered over 18 months via a blended learning model, your training will take place via live virtual classroom sessions, one-to-one coaching, online learning and quarterly face-to-face hackathons. You’ll be introduced to core data skills including data modelling, data manipulation and visualisation, data architecture and cloud, data analytics and statistics. At the end of the programme and upon successful completion of your End Point Assessment, you will roll-off into the Thales UK business as a Data Analyst..
Requirements
Essential qualifications
GCSE in:
* 5 GCSEs including Maths and English (grade 9-4 (A-C))
A Level in:
* Any (grade C or above)
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
* Problem solving skills
* Number skills
* Analytical skills
* Logical
* Team working
* Initiative