September 2020
Salary £18,000
Location: Huddersfield
Disciplines: Chemical Engineering, Chemistry, Computing

The company is seeking a school leaver or undergraduate to start with them for 1 full year in their Technology and Engineering (Data Science)  Department - which supports regional chemical manufacturing operations. They are a global company and market leader in agribusiness with sales of $12.8 billion in 2016. Huddersfield Manufacturing Centre is one of their UK chemical production sites and specialises in high volume batch products for the agricultural sector. The Site employs over 350 people and operates 7 production plants, utilising complex chemical processes demanding a broad range of engineering support service. The site has won a number of nationally recognised awards, in particular for its effective engineering, awarded by the Chemical Industries Association.


The Technology and Engineering department provides support and services to the manufacturing plants primarily in the fields of Process Engineering and Chemistry. It includes optimisation of throughput, efficiency and quality, troubleshooting and operational improvements. It also ensures a high standard of health, safety and environmental performance and deals with the requirements of regulatory authorities to ensure compliance with rules and guidelines.



Data Scientist

The successful student will spend the year working with a Data Science Specialist, where they will support teams in the manufacturing environment, working to provide timely information for production troubleshooting and process development.


Induction and appropriate training will be provided.


Previous students have been recognised as regional winners of the Year in Industry ‘Contribution to Business Awards’ with projects including; the rationalisation and redesign of a methanol delivery system, and optimisation of a solvent recovery unit.


Students will learn technical and team working skills and will interface with people at all levels within the organisation. We offer a positive learning experience for the right candidate who has a passion for driving the best from a manufacturing environment and seeing tangible outputs from their efforts.



Safe and reliable chemical manufacturing requires data to demonstrate the manufacturing process is understood and controlled. The data science role is to help convert data into information and models that give the production teams insight into their processes.


The student will work with the Data Science Specialist, ensuring that data collected can answer the problem at hand, manipulate it to provide information and report the findings in an accessible way. The student will be working on live problems on our processes and so requires the ability to pick up topics and any necessary theory quickly.


We expect students to have a grasp of basic programming concepts and a willingness to learn a new programming language (support for learning the required packages will be provided). Experience creating apps or software will be an advantage.


Good interpersonal skills are required as students will participate in problem identification sessions with company personnel at all levels from technicians to senior managers. This is an important step in the process to ensure the correct question is being answered.


The data science role is very varied and provides opportunities to share work externally. Topics presented previously include Insights into process deviations using multivariate control charts; visual exploration of datasets using self-assembling graphs; digital twin of a manufacturing process; and using simulation methods to mitigate supply chain risk.


To apply for this placement or for more information, please contact Caroline Jardine-Smith at stating your interest, your full name and the vacancy reference.
Please note, you must be fully registered with The YINI scheme to apply. 
See the YINI application page to complete an on-line application form if you are not already registered.

090CJSNW Student Data Scientist, Huddersfield, West Yorkshire

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