Clinical Engineering Apprentice (Data Scientist, Clinical Engineering)

Wage: £24,465 a year
Training course: Data scientist (integrated degree) (level 6)
Hours: Monday - Friday generally, however, will be required to work flexibly to meet unpredictable demands on the service.
Start date: Saturday 30 May 2026
Duration: 4 years
Positions available: 1

Summary

The successful candidate will be enrolled onto the Level 6 Apprenticeship Standard - Data scientist (integrated degree) and upon successful completion will achieve a BSc (Hons) Data Science.

Wage £24,465 a year Check minimum wage rates (opens in new tab) Training course Data scientist (integrated degree) (level 6) Hours Monday - Friday generally, however, will be required to work flexibly to meet unpredictable demands on the service. 37 hours 30 minutes a week Start date Saturday 30 May 2026 Duration 4 years Positions available 1

What you'll do at work

Observe, learn and assist, under supervision, in the full range of work in the Clinical Engineering Department.

This work will include:

Device safety for patients and staff Planned preventative/corrective maintenance Inventory management Medical device lifecycle management Acceptance and safety testing Medical device decommissioning Assistance in the maintenance of records Equipment evaluation, development and audit Complete the Clinical Apprentice Logbook, feedback forms and reflective forms as required Ensure cleaning, calibration, safety checks and maintenance of medical devices and test equipment is carried out as instructed and in strict compliance with instructions Maintain accurate records of work undertaken

Where you'll work

New Cross HospitalWolverhampton RoadHeath TownWolverhamptonWV10 0QP

Training

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

What you'll learn

Course contents Identify and clarify problems an organisation faces, and reformulate them into Data Science problems. Devise solutions and make decisions in context by seeking feedback from stakeholders. Apply scientific methods through experiment design, measurement, hypothesis testing and delivery of results.  Collaborate with colleagues to gather requirements.Perform data engineering: create and handle datasets for analysis. Use tools and techniques to source, access, explore, profile, pipeline, combine, transform and store data, and apply governance (quality control, security, privacy) to data.Identify and use an appropriate range of programming languages and tools for data manipulation, analysis, visualisation, and system integration. Select appropriate data structures and algorithms for the problem.  Develop reproducible analysis and robust code, working in accordance with software development standards, including security, accessibility, code quality and version control.Use analysis and models to inform and improve organisational outcomes, building models and validating results with statistical testing: perform statistical analysis, correlation vs causation, feature selection and engineering, machine learning, optimisation, and simulations, using the appropriate techniques for the problem.Implement data solutions, using relevant software engineering architectures and design patterns. Evaluate Cloud vs. on-premise deployment.  Determine the implicit and explicit value of data. Assess value for money and Return on Investment.  Scale a system up/out. Evaluate emerging trends and new approaches. Compare the pros and cons of software applications and techniques.Find, present, communicate and disseminate outputs effectively and with high impact through creative storytelling, tailoring the message for the audience. Use the best medium for each audience, such as technical writing, reporting and dashboards.  Visualise data to tell compelling and actionable narratives.  Make recommendations to decision makers to contribute towards the achievement of organisation goals.Develop and maintain collaborative relationships at strategic and operational levels, using methods of organisational empathy (human, organisation and technical) and build relationships through active listening and trust development.Use project delivery techniques and tools appropriate to their Data Science project and organisation. Plan, organise and manage resources to successfully run a small Data Science project, achieve organisational goals and enable effective change.

Training schedule

This training schedule has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.

Essential qualifications

GCSE in:

English (grade C/4)Maths (grade C/4)

BTEC in:

Engineering (grade Pass)

Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.

Skills

Communication skillsIT skillsAttention to detailOrganisation skillsCustomer care skillsProblem solving skillsPresentation skillsAdministrative skillsNumber skillsAnalytical skillsLogicalTeam workingCreativeInitiativeNon judgementalPatienceMotivatedHigh level of manual dexterity

About this employer

The Royal Wolverhampton NHS Trust is one of the largest NHS Trusts in the West Midlands providing primary, acute and community services. We have been nationally recognised for providing excellence in healthcare; we are home to the busiest and most technologically advanced Cardiac Centre in the West Midlands.

After this apprenticeship

Depending on the route of the successful candidate this may lead to a future progressive pathway within the CIS team, Clinical Engineering