Data Scientist Degree Apprenticeship
Our Data Scientist Degree Apprenticeship enables organisations to future‑proof their workforce, building in‑house data science capability that improves efficiency, strengthens decision‑making and unlocks the full value of organisational data.
Designed for organisations that want to develop high‑performance data teams, this programme equips new recruits and existing employees with advanced skills in analytics, machine learning, big data technologies and professional data practice. Apprentices apply their learning directly to live business challenges, delivering measurable impact from the outset while developing the knowledge, skills and behaviours needed to drive digital transformation.
By investing in this apprenticeship, employers strengthen their data science talent pipeline, boost productivity, embed best‑practice methods, and accelerate progress towards evidence‑led, efficient and scalable ways of working in one of the UK’s fastest growing fields.
Fact file
| 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.
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| Entry requirements |
Grade 5 in GCSE Mathematics or equivalent, Grade 4 in GCSE English Language or equivalent (prior to admission)
with
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.
We strongly recommend contacting our Employer Engagment Team to discuss the suitability of this programme for your staff.
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| Eligibility requirements |
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 Apprenticeship Standard.
- work a minimum of 50% of their time in England
- have access to the off-the-job training detailed in their individual learning plan
- be a UK/EU/EEA national or have lived and have had a right to work in the UK for 3 years or more
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.
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| Start date |
September 2026
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| Application deadline |
Mid-July 2026
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| Programme fees |
£19,000
Programme fees are paid by the employer either via the apprenticeship levy or they may be eligible for up to 100% co-investment from the government, there is no cost to the apprentice. Read the funding information to find out more.
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| Campus |
University Park, Nottingham |
Who is the Data Scientist Degree Apprenticeship for?
Our Data Scientist Degree Apprenticeship programme offers businesses a cost-effective way to attract and develop new talent or upskill existing staff.
Apprentices must be employed in a job role that provides opportunities to learn the skills, knowledge and behaviours outlined in the Data Scientist Degree Apprenticeship Standard. They must also work at least 50% of their time in England.
We acknowledge that apprentices will come to this programme from a variety of educational backgrounds and job roles; for example, some apprentices may have prior mathematical skills knowledge.
We work with each apprentice to determine their level of existing skills and knowledge and build a learning plan to provide the support they require to meet the apprenticeship standard.
Read more about eligibility for degree apprenticeships.
“Our apprentice understands our business and data science and can act as the link between the two.
By developing our apprentice at the university, with a new network and input from new people, they can develop skills and knowledge we don’t have in-house. It’s another string to our bow.
Our market is changing, and our customer needs are changing. Having a data scientist who can apply what they’re being taught, whether that’s mathematical models, technical skills or the systems they’re using, is going to make a difference to our service offering going forwards and make our offer more aligned with our bigger competitors."
Jon Harris, Director, Dalecourt
Programme details
The Data Scientist Degree Apprenticeship is delivered by block release via blended learning, with each year further building on the apprentice’s knowledge and skills. The programme is typically delivered over a three-year period, followed by gateway review and end-point assessment, upon successful compleition apprentices will be awarded a BSc (Hons) Data Science Degree and Apprenticeship Certificate.
Read Hassan's story, a Data Scientist Degree Apprentice alumni, and find out how the programme has helped him to grow his career and make a real difference to his organisation.
Modules
The first year of our Data Scientist Degree Apprenticeship is designed to develop core analytical, technical and professional competence.
Apprentices develop the core skills needed to work confidently with data in real organisational settings. The focus is on turning mathematical, analytical and programming fundamentals into practical capability that supports day-to‑day decision‑making in the workplace. Year one establishes the essential toolkit on which more advanced data science, machine learning and strategic analytical skills will be built in later years.
What apprentices learn
Statistical analysis: Understanding uncertainty, identifying trends and producing evidence-based insights.
Programming for data: Writing clean, reproducible code to collect, manage and analyse real-world datasets.
Applied analytics: Using mathematical and computational thinking to solve practical data problems and understand how machine learning techniques are built.
Professional practice: Reflecting on progress, developing key behaviours, and preparing for End Point Assessment.
Workplace impact
By the end of the year, Data Scientist apprentices can:
- Apply statistical methods to real business questions
- Clean, model and analyse data using professional tools
- Work across the data pipeline, from data access to insight generation
- Communicate findings clearly and ethically
Modules
- Probability and Statistics for Data Analysis (30 credits)
- Software Development for Data Analysis (40 credits)
- Applied Data Analytics (40 credits)
- Becoming a Data Analyst (10 credits)
In year two, apprentices move beyond the fundamentals to apply advanced data science techniques to real organisational challenges. The focus shifts from building core capability to using it in authentic, end-to‑end projects, developing greater independence, confidence and professional readiness. Year two prepares apprentices to step up as capable, independent data scientists, ready for advanced responsibilities and the final stage of their apprenticeship.
What apprentices learn
Advanced statistics & modelling: Time series, forecasting, stochastic processes and multivariate analysis.
AI & machine learning: Neural networks, deep learning and optimisation techniques applied to real datasets.
Collaborative project delivery: Working in agile teams to design, build and present a complete data science solution.
Professional development: Reflecting on progress and preparing for the end-point assessment.
Workplace impact
By the end of year two, apprentices can:
- Develop predictive and AI‑driven models
- Build and deliver full data science workflows in a team
- Apply advanced methods to complex business problems
- Communicate technical decisions with confidence
Modules
- Data Science Group Project (40 credits)
- Statistics and Probability Modelling (40 credits)
- AI and Machine Learning (20 credits)
- Becoming a Data Scientist (20 credits)
In year three, apprentices move into fully independent, professional‑level data science practice. The focus is on delivering real organisational impact, working with large‑scale data technologies, and preparing for the end-point assessment. Year three consolidates learning across the programme, supporting apprentices to transition into fully capable, workplace‑ready data scientists.
The Work‑based Project is the capstone learning experience of the programme, giving apprentices the opportunity to design and deliver a substantial data science solution within their organisation. Acting as an independent practitioner, the apprentice applies the full breadth of knowledge, skills and behaviours developed across the programme to tackle a meaningful business challenge. Through planning, research, advanced analysis and clear communication, they demonstrate professional competence, ethical practice and real organisational impact. It’s a chance for apprentices to solve meaningful problems inside your business, supported by academic experts, while you gain high‑quality analysis tailored to your strategic goals.
What apprentices learn
‘Big Data’ techniques: Distributed and parallel processing using tools like Apache Spark.
Scalable analytics: Designing data workflows capable of handling complex, high‑volume datasets.
Work-based project delivery: Planning and completing a major data science project within their organisation.
Professional preparation: Building a portfolio, refining their CV, and preparing for the end-point assessment.
Workplace impact
By the end of year three, apprentices can:
- Build scalable data pipelines for large datasets
- Deliver substantial, high‑value projects that solve real business challenges
- Demonstrate advanced technical and analytical capability
- Present their work professionally and confidently ready for EPA
- Step into data scientist roles with autonomy and readiness
Modules
- Scaling up Data Science (20 credits)
- Work-based Project (40 credits)
Once the apprentice has completed all their on-programme learning, a meeting will take place between their employer and the university. During this meeting, the apprentice’s knowledge, skills and behaviours will be assessed to determine whether they have met the minimum requirements set out in the Data Scientist Degree Apprenticeship standard. Apprentices deemed to have met these requirements will progress onto the end-point assessment (EPA).
End-point assessment (EPA)
The end-point assessment is the final, integrated assessment for the Data Scientist Degree Apprenticeship. It provides a synoptic evaluation of the knowledge, skills and behaviours (KSBs) apprentices have developed throughout the programme and confirms their readiness to perform as competent professional data scientists.
The EPA consists of three assessment components:
Knowledge Test
A structured exam assessing core data science principles, methods and professional standards. This ensures apprentices can apply theoretical understanding to a range of analytical and organisational scenarios.
Work-Based Project Report
A written report based on a substantial project completed within the apprentice’s organisation. This demonstrates the ability to design, deliver and evaluate a real data science solution, showing how academic learning has been applied to produce meaningful workplace impact.
Professional Discussion (Portfolio‑Informed)
A structured conversation with assessors, drawing on evidence from the apprentice’s portfolio. This explores technical decision‑making, professional behaviours, ethical practice and the apprentice’s holistic contribution as a data scientist.
Completion of all three elements confirms occupational competence and marks the successful conclusion of both the apprenticeship and the degree. The EPA must be undertaken within six months of passing the Gateway, in line with official assessment guidance.
The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules (including methods of assessment) may be changed, renamed, reorganised or or be updated, or modules may be cancelled, over the duration of the programme due to a number of reasons such as curriculum developments, or staffing changes or changing demands of industry. The university shall ensure that modules and programme continue to adhere to the Knowledge, Skills and Behaviours (KSB) required of the applicable Apprenticeship Standard, which are fundamental to any programme of delivery. This content was last updated on Tuesday 21 April 2026.
Why choose the Data Scientist Degree Apprenticeship at the 海角黑料?
Our School of Computer Science in ranked number 1 in the UK for its research environment (Research Excellence Framework 2021) connecting apprentices with cutting-edge thinking across data science, computing and applied analytics.
On-programme employers rate us as 'excellent' as a training provider for our degree apprenticeship provision .*
By working together, we equip your apprentices with the core knowledge, skills and behaviours your industry needs to compete and succeed at the highest level.
*As per the gov.uk website April 2026
“Embarking on an apprenticeship has been one of the best decisions I have made. It has allowed me to grow personally and professionally, meet exceptional people, and widen my career aspirations.”
Luca Smith, Data Scientist Degree Apprentice, Experian
Apprenticeship features
Skills Scan
As part of the application and enrolment process, we carry out a skills scan with the apprentice and their line manager. This enables us to determine apprentices' existing levels of skill and knowledge and build a personal plan which will set out all the learning, tutorial support, and resources provided by the university.
Tripartite reviews
As part of our continued support for apprentices and the degree apprenticeship, we offer tripartite reviews between employer, apprentice and the university to formally assess progress in the academic programme and work-based learning.
Assessment
Apprentices are assessed through a mixture of work-based projects, in class tests, coursework, group work and a portfolio. The degree apprenticeship also includes gateway review and end-point assessment. Several of the assessments are synoptic, providing the opportunity for work-based examples to demonstrate the application of the knowledge, skills and behaviours gained from off-the-job training.
Support team
Each of our Degree Apprenticeship programmes are designed to include full support for the apprentice and their employer. We provide:
- an Account Manager to support and guide employers throughout the programme
- a Degree Apprenticeship Officer to support each apprentice throughout the programme
- an assigned Academic Tutor/Skills Tutor for each apprentice