Yokohama Nissan Motor Full time
Data Science is a broad and fast-moving field spanning maths and statistics, software engineering and communications.

As a Data Science Apprentice at Nissan Sunderland, you will join a Digital Innovation team within business functions including Engineering, Supply Chain Management or Quality Assurance. Each team is dedicated to using the latest digital technologies to improve our manufacturing process and support the factory to produce cars.

You will learn and use skills like data visualisation, programming, data cleaning and transformation, project management and training artificial intelligence models.

A perfect fit for this role should bring strong communication skills and the ability to build relationships with project stakeholders. You should have a good eye for detail and be motivated to grow and develop new skills.

You will acquire the skills and knowledge to work as a member of a team responsible for exploiting Nissan digital manufacturing data for improvement activities across the factory.

At the end of your Degree Apprenticeship, you will achieve a Data Analyst Degree Apprenticeship (Digital and Technology Solutions Professional L6) and have the opportunity to work on cutting edge data tools and AI challenges in the industry.

Key requirements include 120 UCAS points, A Level Maths (Grade A-B) or equivalent, plus two additional A Level STEM or Computer Sciences subjects (Grade A-B) or equivalent, permission to live and work in the UK without restriction, a willingness to learn with a passion for Mathematics, Data and Digital Technology, strong analytical skills, excellent communication, creative and forward thinking, and the ability to adapt to a fast-paced organization.

  • Yokohama Nissan Motor Full time

    Job Ref: R00156875 Data Science Degree Apprenticeship (start Sept 2024) · Nissan Sunderland Data Science Degree Apprenticeship · Data Science is a broad and fast-moving field spanning maths and statistics, software engineering and communications. · As a Data Science Apprent ...


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