University partners with Zurich to launch data science degree apprenticeship to future proof workforce

21 Oct 2020

The University of Winchester has designed and launched a data science degree apprenticeship with leading insurer Zurich UK as part of a drive to future-proof its workforce. The three-year course has opened to students for the first time.

As technology transforms the insurance industry, Zurich is upskilling and reskilling employees in fields such as AI, automation and data science.

Data science - which blends maths and computing - is one of the world's fastest growing careers, ranked third in LinkedIn's 2020 Emerging Jobs report. Insurers are using it to glean insights from internal and external data to better manage risk.

But when Zurich struggled to find a comprehensive course in the field, it linked-up with the University of Winchester to create a new one.

The University of Winchester's subject experts worked with Zurich's data scientists to develop the course content. This was blended with the University's existing data science degree to create a new Bachelor of Science degree apprenticeship.

Seven of Zurich's employees are among the first cohort embarking on the course, which is open to students across England.

Stella McKnight, Director of Employer Partnerships at the University of Winchester, said: "Degree apprenticeships have become important development programmes for employers in both attracting new talent and in developing and retaining their existing talent. The University of Winchester is committed to employer-led learning. There has been strong collaboration with Zurich and the University throughout to create a clear progression route for their apprentices. The structure and design of this specialist Data Science Degree Apprenticeship programme combines academic learning with on-the-job learning with emphasis placed on blending new knowledge with practical application of skills in the workplace.

"Winchester is also currently working in partnership with other businesses to deliver degree apprenticeship schemes to further build the skills of the workforce and support in preparing for future skills shortages such as in data science, cyber, business analysis and digital technologies."

Anita Fernqvist, Zurich's UK Chief Data Officer and Director of Operations said: "The insurance industry is undergoing a radical, tech-driven transformation which is changing the way we work and creating new roles alongside traditional careers. This apprenticeship gives our employees - some of who may not have had a chance to gain a degree - an opportunity to re-skill or up-skill as data scientists. By building on the talents of our existing employees, we can help people to develop sustainable careers and future-proof our workforce."

Students will cover 14 modules across three areas: data analytics, computer science and software engineering and mathematics and statistics. Candidates will learn everything they need, from the fundamental mathematics behind algorithms to writing efficient code for the latest cloud computing systems.

Zurich's employees will spend one day a week at the University of Winchester Business School, and the rest applying what they learn at work.

Case study
Hannah Lee, 22, a Junior Data Scientist, is among the first Zurich employees embarking on the course. Hannah joined Zurich after completing her A-levels, where she started out as an Insight Analyst. Explaining why she has chosen to study on the course, she says: "Data science involves solving complex problems using a variety of analytical tools and techniques. It has real business impact. I've been able to learn so much on the job. This course will help me understand the maths and theory behind some of the techniques we use, as well as learning new skills that I can apply to my role."

If you are an employer wishing to source further information about degree apprenticeships at the University of Winchester, please contact Stella McKnight: Stella.McKnight@winchester.ac.uk. More information at: www.winchester.ac.uk/degreeapprenticeships

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