We need to make the seas safe.

For our warships, for civilian ships, for everyone. And that’s where you come in. You’ll be at the heart of these missions whether they’re in a Mediterranean port, or on operations in the Persian Gulf. As a Mine Warfare Specialist you’ll lead the way for our fleet, clearing any mines in its path.

Wage: £20,400 a year

• An excellent pension scheme
• Subsidised travel and accommodation
• Six weeks of paid holiday every year
• Free medical and dental care

Training course: Data technician (level 3)

Hours: Shifts to be confirmed, total hours per week: 40.00

Start date: Friday 2 August 2030

Duration: 1 year 6 months

Positions available: 28

Most of your apprenticeship is spent working.

You’ll learn on the job by getting hands-on experience.

What you'll do at work

• Make sure our missions are possible whatever they’re for, from delivering essential humanitarian aid, to embarking on conflict operations.
• Find mines using sonar, and then launch remote controlled mine disposal vehicles.
• Gain a wide range of skills, from basic seamanship to manning light weaponry
• Be responsible for the safety of your ship and everyone on board
• Stay quick thinking and focused at all times

Where you'll work

Navy Command HQ
The Admiral Sir Henry Leach Building
Portsmouth
Hampshire
PO2 8BY

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

Training provider: ROYAL NAVY

Training course: Data technician (level 3)

What you'll learn

Course contents

• Select and migrate data from already identified sources.
• Format and save datasets.
• Summarise, analyse and explain gathered data.
• Combine data sets from multiple sources and present in format appropriate to the task.
• Use tools and/or apply basic statistical methods to identify trends and patterns in data.
• Identify faults and cleanse data to improve data quality, for example identifying gaps, duplicate entries, outliers and unusual variances, including cross-checking across data elements or between data sources.
• Audit data results for maintenance of data quality, reviewing a data set once all sources are combined, to ensure accuracy, completeness, consistency and traceability from original data.
• Demonstrate the different ways of communicating meaning from data in line with audience requirements.
• Produce clear and consistent documentation of the data provided to others and of actions completed. Where appropriate or mandated by the working context, this documentation should use standard organisational templates.
• Store, manage and distribute data in compliance with organisational, national, sector specific standards and or legislation.
• Considers sustainability and ways to reduce impact. For example, using cloud storage, sharing links to files, avoid storing multiple versions of files, and reducing the use of physical handouts of documentation.
• Parse data against standard formats, and test and assess confidence in the data and its integrity.
• Operate collaboratively in a working context that accounts for, and takes advantage of, the roles, skills and activities of others, especially those interacting with the same data sets or working towards a common goal.
• Prioritise own activities within the context of the duties to be performed, taking account of any known or expected impact on others.
• Follows equity, diversity and inclusion policies in the organisation for a common goal.
• Demonstrate the ability to use different tools and methods to formulate and utilise effective prompts to research, apply, and evaluate data transformation techniques.
• Select and migrate data from already identified sources.
• Format and save datasets.
• Summarise, analyse and explain gathered data.
• Combine data sets from multiple sources and present in format appropriate to the task.
• Use tools and/or apply basic statistical methods to identify trends and patterns in data.
• Identify faults and cleanse data to improve data quality, for example identifying gaps, duplicate entries, outliers and unusual variances, including cross-checking across data elements or between data sources.
• Audit data results for maintenance of data quality, reviewing a data set once all sources are combined, to ensure accuracy, completeness, consistency and traceability from original data.
• Demonstrate the different ways of communicating meaning from data in line with audience requirements.
• Produce clear and consistent documentation of the data provided to others and of actions completed. Where appropriate or mandated by the working context, this documentation should use standard organisational templates.
• Store, manage and distribute data in compliance with organisational, national, sector specific standards and or legislation.
• Considers sustainability and ways to reduce impact. For example, using cloud storage, sharing links to files, avoid storing multiple versions of files, and reducing the use of physical handouts of documentation.
• Parse data against standard formats, and test and assess confidence in the data and its integrity.
• Operate collaboratively in a working context that accounts for, and takes advantage of, the roles, skills and activities of others, especially those interacting with the same data sets or working towards a common goal.
• Prioritise own activities within the context of the duties to be performed, taking account of any known or expected impact on others.
• Follows equity, diversity and inclusion policies in the organisation for a common goal.
• Demonstrate the ability to use different tools and methods to formulate and utilise effective prompts to research, apply, and evaluate data transformation techniques.