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Data Science Apprenticeship
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Are you ready to embark on a rewarding journey within an educational community that values increasing opportunities, improving outcomes for our students. We are looking for a Data Science apprentice to join The Operational Excellent Team.
Key responsibilities:
- Assisting in the collection and organisation of raw data from various sources to support data-driven leadership
- Learning to transform data into usable formats for analysis, ensuring the data is ready for decision-making processes
- Collaborating with the team to validate data quality and helping maintain clean and accurate datasets for reliable insights
- Gaining exposure to database administration tasks and assisting in monitoring and optimising database performance for efficiency
- Learning about data modelling techniques and contributing to the development of data pipelines to streamline data processes
- Documenting processes, procedures, and best practices, as well as assisting in creating data-related reports to communicate findings effectively.
Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.
Where you'll work
The Rock Centre
Lichfield House, 27 31 Lichfield Street
Walsall
WS1 1TJ
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
UNIVERSITY OF NOTTINGHAM, THE
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.
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Training schedule
Qualification:
- BSc (Hons) Data Science
- Duration - 42 months (including EPA period)
- Delivery - Blended learning: combines remote online learning and face to face teaching delivered by block release in Nottingham
Entry requirements:
- Grade 5 in GCSE Mathematics or equivalent
- Grade 4 in GCSE English Language or equivalent (prior to admission)
- BBC at A-Level to include Maths
The following A-Levels are not accepted: Citizenship Skills, General Studies, and Critical Thinking.
Candidates are reviewed on a case-by-case basis enabling employees with lower-level apprenticeships (including Level 4 Data Analyst), a strong mathematical background or substantial work experience with relevant qualifications to be considered. Apprentices’ prior learning may affect the start date of their programme.
All apprentices must:
- Be working in a job role that provides opportunities to apply and develop the knowledge, skills and behaviours from the programme, outlined in the Level 6 Data Scientist Degree Apprenticeship Standard.
- Spend at least 50% of their working hours in England over the duration of the apprenticeship. This also applies to remote and hybrid workers.
- Have access to the off-the-job training detailed in their individual learning plan.
- Must have a valid and eligible residency status and the right to work in England.
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English and maths eligibility requirement English and maths eligibility requirement is assessed based on the apprentice's age at the start of their apprenticeship. Please note that English and maths eligibility requirements do not supersede programme entry requirements.
- Aged 16-18: Apprentices who do not hold a level 2 qualification in English and Maths must study towards and achieve this during their apprenticeship. Funding is available.
- Aged 19+: There is no mandatory requirement to complete Level 2 English and maths. However, apprentices or employers may opt-in for the apprentice to study towards an English and maths qualification if they don't already have an equivalent qualification, with funding available if they choose to do so.
Apprentices who do not provide a suitable Level 2 English certificate, and do not hold an appropriate English language equivalent qualification from this list, will also need to provide an International English Language Testing System (IELTS) result that is dated within the last two years. The minimum requirement for this programme is an overall score of 6.0, with no less than a 5.5 in each of the individual elements. The university’s policy around this can be found here.
Start date - September 2026.
Essential qualifications
- GCSE in:
- English (grade 4)
- Maths (grade 5)
- A Level in:
- All apart from Citizenship Skills, General, Critic (grade B,B,C)
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
After this apprenticeship
Your earnings can increase over time with an apprenticeship. Find out about potential future pay (opens in new tab).
The department leads strategic transformation projects, develops trust-wide digital capability, strengthens communication and engagement, and ensures that technology and data are used purposefully to improve experiences for staff, pupils and families. By combining this expertise with a strong understanding of education, the team helps schools focus on what matters most, delivering outstanding learning opportunities and supporting every child to thrive. Operational Excellence is not simply a support function; it is a catalyst for innovation, continuous improvement and sustainable organisational growth.
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