Level 6 Data Science Degree Apprenticeship

Are you looking for an exciting opportunity to develop cutting-edge data science skills and solve real-world business challenges?

Do you enjoy working with data, uncovering patterns, and using evidence to influence decisions? Are you curious about how artificial intelligence, machine learning, and advanced analytics can help businesses innovate and improve performance? Our Data Scientist Apprenticeship provides an excellent opportunity to launch your career in data science while learning from industry experts within a leading technology company.

Benefits of the programme

• Earn while you learn with a competitive salary.
• Gain hands-on, job-specific training and real-world experience.
• Achieve a recognised professional qualification.
• Secure a permanent role from the start of your apprenticeship
• Enjoy fully funded tuition fees on approved training programmes.
• Learn from experienced professionals and develop skills that will support your long-term career growth.
• Build valuable experience and develop your career in data science

About the Role

As a Data Scientist Apprentice, you will be valued for your curiosity, analytical mindset, and passion for solving problems using data. You will work with a variety of datasets, tools, and technologies to identify trends, build predictive models, and generate insights that support business decision-making.

Working alongside experienced data professionals, you will learn how to transform raw data into valuable business intelligence and help develop data-driven solutions that create measurable impact.

Your responsibilities may include:

• Identifying business challenges and using data science techniques to recommend solutions.
• Collecting, preparing, cleansing, and analysing data from multiple sources.
• Building skills in: Data Science and Analytics; Machine Learning and Artificial Intelligence; Statistical Analysis; Data Engineering Fundamentals; Data Visualisation and Storytelling; Programming and Automation (e.g. Python, SQL)
• Supporting the development and testing of predictive models and analytical solutions.
• Working with data teams to create data products, dashboards, and insights used across the business.
• Evaluating model performance and supporting continuous improvement of analytical solutions.

What You Will Learn

Throughout the apprenticeship, you will gain experience and knowledge in:

• Data collection, preparation, and management techniques.
• Statistical methods and hypothesis testing.
• Programming languages such as Python and SQL.
• Machine learning concepts and model development.
• Data visualisation and storytelling techniques.
• Exploratory and predictive analytics.
• Artificial Intelligence fundamentals and responsible AI practices.
• Data governance, ethics, and compliance.
• Cloud-based analytics and data science platforms.
• Business and stakeholder engagement skills.
• Communicating technical findings to both technical and non-technical audiences.
• Project management and agile ways of working.

Apprenticeship Programme

You will study towards a Level 6 Data Scientist Apprenticeship with The University of Nottingham.

The programme is delivered over 42 months through a blend of:

• On-campus learning
• Online study
• Workplace-based learning

You will typically attend university for a minimum of 4 weeks each academic year, delivered in 1-week blocks.

On successful completion of the programme and End Point Assessment, you will achieve:

• A fully funded BSc (Hons) Data Science degree
• A Level 6 Data Scientist Degree Apprenticeship qualification

Entry Requirements

To apply, you will need:

A Levels

• 3 A levels (BBC) including Maths (Citizenship Skills, General Studies and Critical Thinking are not accepted)
• Or a Level 4 Data Analyst qualification will be considered on a case-by-case basis

GCSEs

• Minimum of five GCSEs at Grade 4/C or above (Maths at Grade 5/C or above)
• Must include: English Language; Mathematics

Please note that those with a relevant degree will not be eligible for this programme.

Benefits

• Competitive salary of £24,000 per annum
• Performance-related pay uplifts
• Holiday entitlement of 201 hours a year (plus a company day and bank holidays)
• Contributory Company Pension
• Health Care Cash Plan
• Hybrid/flexible working options
• Employee assistance programme
• Learning and development support
• Employee discounts and wellbeing initiatives
• Life Cover
• 80 Hours Volunteering per year (first two years)

For further information about our Future Talent recruitment process, including hints and tips, or to connect with a member of the Future Talent Team, a Graduate, or an Apprentice, please visit Thales Future Talent - Connectr.

Please note, assessment centres for shortlisted candidates will be held between February - May 2027. Induction week for all Graduate and Apprentices will take place from Monday 6 September - Friday 10 September 2027.

Closing date: Our applications will close at 11.59pm on Wednesday 17 February 2027, this is the only time we will be accepting applications this year. Please note, we will be in contact by the end of February 2027 with details of next steps.

PLEASE NOTE THAT ROLES MAY CLOSE EARLIER THAN THE ADVERTISED DEADLINE IF WE RECEIVE A HIGH NUMER OF APPLICATIONS. WE ENCOURAGE YOU TO APPLY AS SOON AS POSSIBLE TO AVOID MISSING OUT ON THIS OPPORTUNITY.

Because of the work we do at Thales, all roles are subject to security requirements.

To be considered for this position, you must have the permanent right to work in the UK and be able to successfully complete and maintain UK Government security checks, including Baseline Personnel Security Standard (BPSS) screening and Security Clearance (SC), which is a government background check, before starting employment.

To be eligible for SC clearance, you will typically need to have lived in the UK continuously for the last five years. As part of the vetting process, you will be asked to provide evidence of your identity, right to work in the UK, any time spent overseas during the last five years, and your employment and/or education history.

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