Digital Modelling Engineer

Vacancy: Digital Modelling Engineer Location: UK Flexible Job Family: Commercial Our Efficient Natural Resources Sector is currently running a transformation programme to support the execution of the sector strategy using digital tools and technology. We are currently recruiting for a Digital Modelling Engineer to develop and provide data-driven solutions to improve process understanding and implement for the control and performance improvement of JM's process technologies. The successful candidate will be responsible for managing the associated data workflow (collaboration with JMIT) as well as pre-processing of the data (reconciliation, cleaning), feature selection and building digital models using multivariate statistics and machine learning methods. This role exists to grow our internal capability to apply data-driven solutions to existing and new business problems in order to help us achieve our sector strategy, as well as contribute to driving development of JM's capabilities in digital modelling approaches and their application to improving our operations and supporting our customers. Key responsibilities: Work collaboratively to deliver and improve JM's capability in data-driven process modelling and control as the key enabling technology to improve the services that we provide to our customers Undertake specific projects by data processing, analysis and statistical / machine learning modelling to provide insight for operations improvement and to deliver options for data-driven model-based control Play an active role in the development of statistical and machine learning models of catalyst customer and licensed technology processes, helping to deliver the digital platform for growth generating customer insights and recommendations to improve performance Collaborate with manufacturing technology research and/or development to develop reduced order models based on combined first principles and data-driven approaches to aid the design and scale up of key process technologies Work collaboratively with the Core Engineering and Smart Manufacturing team at Chilton to deliver digital solutions to the sectors for process management, operations improvements and process control Support and collaborate with the Measurement & Control team and with JMIT to develop and implement data workflows that enable the introduction of new measurements as well as the generation of data structures that enable better data-driven approaches to process monitoring and process control Work with the Product Owner(s) and Product Manager in each area to understand requirements, develop hypotheses and then test and implement measurement and control innovations Work with other business stakeholders and JMIT to 'productionise' models so that they can be built into service offerings for JM Track actions, remove blockers and coordinate planning activities for new initiatives and experiments Track and report on success metrics and KPIs for experiments Produce communications events for sector staff on new digital capabilities Prepare technical and research reports to communicate outcomes and findings back into the business Are you the ideal candidate? You will have: Degree in Chemical Engineering (preferred), Chemistry, Electrical Engineering, Mathematics or other related discipline Experience in processing large data sets and coding for data manipulation Experience in modelling, preferably use of multi-variate statistics and/or machine learning Data manipulation, processing and coding skills Manufacturing process understanding (ability to interpret plant data from process) is desirable Experience in catalyst or materials research and/or JM-related manufacturing processes is desirable How to apply: If you have the necessary skills and experience to join our team, please apply online. Closing date for applications: 24 September 2021 Johnson Matthey Plc is an equal opportunities employer and positively encourages applications from suitably qualified and eligible candidates regardless of sex, race, disability, age, sexual orientation, marriage or civil partnership, pregnancy or maternity, religion or belief. This job was originally posted as

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