Data Scientist – Level 6 Apprenticeship
Job in
Reading, Berkshire, RG1, England, UK
Listed on 2026-10-16
Listing for:
AWE
Apprenticeship/Internship
position Listed on 2026-10-16
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer, Data Analyst
Job Description & How to Apply Below
Use data to solve real problems and support better decisions. You’ll build skills in statistics, analytics, programming, artificial intelligence and responsible use of data while supporting projects across engineering, science, operations and corporate teams.
At a glanceEntry requirement
- Total of 104 UCAS points.
- A Level Mathematics at Grade C or above, or equivalent, plus a second STEM-related A Level at Grade C or above, or equivalent.
- Candidates with Grade B or above in Mathematics are particularly encouraged to apply.
Security clearance
- Applicants must be British Nationals and aged 18 or over by 31 August 2027.
- You must be willing and able to obtain and maintain the required security clearance.
Working pattern
- Onsite apprenticeship based at AWE Aldermaston and/or Burghfield, with every other Friday off.
Key dates
- Applications close: 8 November 2026
- Assessment centre: 16 February 2027
- Start date:
1 September 2027
This is an onsite apprenticeship. Being onsite will help you learn directly from experienced data scientists, analysts, engineers and technical specialists while working on real business problems.
The key skills we’re looking for- Curiosity with data: You enjoy spotting patterns, asking questions and using evidence to solve problems.
- Technical interest: You are interested in maths, statistics, programming, software, AI, engineering or science.
- Clear communication: You can explain information in a way that helps people understand and act on it.
- Responsible thinking: You understand that data and AI must be used safely, fairly and carefully.
When you complete your apprenticeship, you may be able to move into a Data Scientist role in areas such as applied statistics, advanced analytics, artificial intelligence, machine learning, data engineering or data management.
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