Applied Data Science Intern

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Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions.

Applied Data Science Intern

Apply now for the position of Applied Data Science Intern and gain hands-on experience applying data and digital technologies to solve real engineering challenges at one of the world’s leading healthcare companies.

At Siemens Healthineers Magnet Technology in Oxfordshire, we design and manufacture superconducting magnets for MRI systems. Our manufacturing processes generate large volumes of data from real equipment and systems, giving you the opportunity to explore how data analytics, software and emerging technologies can help us understand and improve the way we manufacture.

This is an exciting time to join us. Alongside our established facility in Eynsham, we are ramping up production at our newly built facility in Bicester. Based mainly in Bicester, you’ll work with teams across both locations and gain insight into how a large-scale business manages the transition of operations while maintaining day-to-day delivery, and how data-driven insights can help improve processes and support better decision-making.

This 12 month internship placement will give you real responsibility within our Engineering teams, contributing to manufacturing and digitalisation projects while developing your technical skills through practical industry experience.

In this role you will:

• Work alongside engineers to analyse manufacturing and process data, helping to identify trends, investigate problems and improve performance.
• Build your understanding of our manufacturing processes and the engineering behind the data, helping you turn real-world measurements into meaningful insights.
• Develop dashboards, reports and data visualisations to help teams better understand their processes and make informed decisions.
• Support the digitalisation of manufacturing processes by helping to develop applications, automate tasks and improve existing workflows.
• Use data analysis and statistical techniques to investigate engineering challenges and identify opportunities for improvement.
• Gain exposure to emerging technologies such as AI, machine learning and predictive analytics, exploring how they could be applied within manufacturing.
• Collaborate with different teams to understand their challenges and develop practical, data-led solutions.
• Take part in engineering projects, analyse results and share your findings through presentations, reports and demonstrations.

All of our interns also participate in our structured 12 month Intern Development Programme, developing professional skills such as communication, teamwork and commercial awareness alongside the technical experience gained within the role.

Work Experience

• You will be currently studying towards a degree in Engineering, Physical Sciences, Data Science, Computer Science, Mathematics or a related discipline, and completing a 12 month industrial placement or sandwich year as part of your degree.
• Your studies or experience should give you some understanding of engineering, physical systems or manufacturing processes, alongside an interest in applying data and digital technologies to real-world problems.
• You will have some experience of programming, data analysis or working with datasets, gained through your university studies, projects or personal interests.
• You will have strong analytical and problem-solving skills, with a curiosity to understand how things work.
• You will have good communication and interpersonal skills, with the ability to work both independently and collaboratively as part of a team.
• You will need to be proactive, with a willingness to learn new technologies, take initiative and develop your technical skills.

Benefits

• 26 days' holiday with the option to buy or sell an additional 5
• Up to 10% employer pension contribution
• Share and bonus scheme
• Access to our flexible benefits from private medical insurance to dental cover
• Corporate Social Responsibility opportunities including 2 paid volunteering days per year and support from our 24/7 employee assistance programme

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