Building skills for life through Data Science: Daniel’s apprenticeship journey

Hear Daniel's story, as a Level 6 Data Science Degree Apprentice at ARU, working within Adult Social Care and Housing.

For Daniel, a career in data wasn’t something he planned, it evolved through curiosity, experience and a willingness to learn. Today, as a Level 6 Data Science degree apprentice at ARU, working within Adult Social Care and Housing at Central Bedfordshire Council, Daniel is taking a structured step forward to strengthen his skills for the long term.

After completing a degree in Philosophy and Politics, Daniel initially joined a management training scheme, believing it would offer the right career path. It soon became clear that it wasn’t the right fit. Following a short period of unemployment, he took a temporary role as a business analyst at a county council, a move that proved to be transformational.

“I haven’t looked back since,” Daniel reflects.

Why an Apprenticeship?

Over the years, Daniel developed his data analysis skills organically, teaching himself new tools and techniques as the need arose. While this approach helped him grow, he began to recognise the value of stepping back and building his expertise in a more structured and holistic way.

“I wanted to fill in the gaps and learn good practice, rather than continuing with an ad-hoc approach,” he explains.

A degree apprenticeship offered the ideal solution, combining academic learning with real-world application, while allowing him to continue contributing to his role at Central Bedfordshire Council. It also provided an opportunity to network with analysts working in different sectors and to evidence his learning more clearly.

Learning that fits the role

Daniel’s apprenticeship is delivered over four years and is primarily taught through online lectures and workshops, complemented by in-person block teaching weeks at ARU’s Cambridge campus each term. These residential weeks provide valuable opportunities to engage directly with tutors and connect with fellow apprentices.

Each module is assessed individually, alongside a portfolio of project work designed to align closely with Daniel’s day-to-day responsibilities. While balancing work and study requires careful time management, Daniel is supported by a flexible approach from his manager, enabling him to meet the 20% off-the-job learning requirement.

Developing skills for life

The apprenticeship has already provided Daniel with a strong grounding in key technical tools such as Python and SQL, alongside core principles of software development, testing and data science best practice. As the programme progresses, he will also explore areas such as data architecture and machine learning.

While not every technical element directly maps to the tools currently used within his organisation, the broader principles have had immediate impact.

“The theory and foundations have enhanced how I approach my day job,” Daniel says, “from improving data processes to thinking more critically about how information can be used.”

Beyond technical capability, the apprenticeship has strengthened Daniel’s confidence, analytical thinking and ability to adapt, skills that will remain valuable throughout his career in a fast-evolving field.

Looking ahead

As data science continues to develop at pace, Daniel knows that ongoing learning will be essential. Through his apprenticeship, he feels equipped not just with new knowledge, but with the mindset and foundations needed to stay current.

“This apprenticeship is giving me the grounding I need to develop my career in a well-rounded way,” he reflects.

During National Apprenticeship Week 2026, Daniel’s journey highlights how apprenticeships truly deliver skills for life, supporting individuals to grow, organisations to innovate, and sectors to build sustainable expertise for the future.