Data Scientist Degree Apprentice within Field Quality

BENTLEY MOTORS LIMITED

Cheshire (CW1 3PL)

Closes in 10 days (Friday 20 February 2026)

Posted on 9 February 2026

Print

Contents

Summary

This role sits within the Quality Function as part of the Field Quality Data Team. You’ll work with technical and non-technical stakeholders to turn diverse data into actionable insights, from dashboards to automated AI pipelines using GenAI. The growing team offers strong development opportunities and exposure across the VW Group.

Wage

£24,929 a year

Check minimum wage rates (opens in new tab)

Training course
Data scientist (integrated degree) (level 6)
Hours
Monday to Friday Shifts to be confirmed

35 hours a week

Start date

Monday 7 September 2026

Duration

3 years

Positions available

1

Work

Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.

What you'll do at work

  • Building dashboards for Quality Functions, from gathering stakeholder requirements through to technical delivery
  • Hands-on development of data pipelines, working with tools such as AWS, KNIME and Snowflake
  • Hands on coding and deployment of ML & AI Models
  •  Cross-functional working with departments such as Aftersales, Production & Marketing, to gain a rounded exposure
  • Supporting delivery of VW Group data products, with opportunities to travel globally
  • Support with the creation of presentations to deliver to Senior Managers and the Board

Where you'll work

Pym's Lane
Crewe
Cheshire
CW1 3PL

Training

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

Training provider

UNIVERSITY OF KEELE

Training course

Data scientist (integrated degree) (level 6)

Understanding apprenticeship levels (opens in new tab)

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.

Requirements

Essential qualifications

GCSE in:

  • English (grade C)
  • Maths (grade C)

Other in:

or equivalent like BTEC Nationals (grade BBC)

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

Skills

  • Communication skills
  • Problem solving skills
  • Number skills
  • Team working
  • Desired Data experience

About this employer

Bentley Motors is a business built on people. Yes, we want to be known for our ideas, our technological innovations, our exceptional products. But none of it is achievable without talented individuals working together to make a diverse and successful team

After this apprenticeship

  • Further progression may well be available in other areas within our sector, upon successful completion of the apprenticeship

Ask a question

The contact for this apprenticeship is:

UNIVERSITY OF KEELE

The reference code for this apprenticeship is VAC2000012598.

Apply now

Closes in 10 days (Friday 20 February 2026)

After signing in, you’ll apply for this apprenticeship on the company's website.