In this role the successful candidate will work alongside a small and growing team of Professional Engineers in new product development and industrialisation of Li-ion batteries and cells. Reporting to the Head of Product Engineering this position will support the capture and analysis of data generated from the production and test of UKBIC baseline and customer products.
The purpose of this role is to deliver data insights that assess impact of manufacturing variation on product performance, thereby determining control measures for critical parameters and process improvement opportunities (manufacture for design), as well as areas opportunities for design tolerances to relax to reduce product unit cost.
As a data scientist the successful candidate will have a good knowledge of data extraction, analysis, statistical regression, modelling, reporting and visualisation tools. The ideal candidate will be:
* Be able to work cross functionally,
* Contribute to issue resolution, root cause investigation, verification and validation activity,
* Participate in internal process meetings by playing a critical role in developing data led decision making.
* Manage and disseminate data to support project activities
* A key enabler towards UKBIC’s Digital Manufacturing strategy.
In summary, the key deliverables for this role are:
* Deliver and report data outcomes to customer and internal programmes, on time and to target.
* Develop, release and continuously improve data modelling capabilities in order to advance insights.
* Develop the tools and platforms that enable the streamlining of delivering data to customer programmes.
* Report modelling methods development and outcomes to retain knowledge and capability within the business.
Key Accountabilities and Responsibilities
* Liaise with engineers and senior management to identify potential concerns and root cause from data sets.
* Make recommendations that will facilitate the continuous improvement of manufacturing processes and systems from the analysis of data that UKBIC will be generating.
* Promote a culture of data driven decision making as well as proactively seek ways to push the understanding on design for manufacture and process improvement opportunities.
* Provide inputs to other analysis tools in the business such as product and process simulation.
* Determining trends between manufacturing data and cell performance to inform and teach in-line checks (such as defect definition and detection) and supplement other predictive tools.
* Determining trends between manufacturing data and failure events/issues – both in product and in process. Failure can include quality non-conformance/not to specification, meeting product requirements or equipment failure and capability issues.
* Work with key stakeholders to receive feedback on data dashboard features, layout, identify critical outputs to ensure data driven decisions are made efficiently.
Required Qualifications, Skills & Experience:
* Degree qualification in relevant Engineering or Science discipline (such as but not limited to Computer Science, Mathematics, Mechanical/Chemical Engineering, Physics).
* Relevant industry experience where advanced analytics is demonstrated (Automotive & Motorsport, Battery or Semiconductor Manufacturing, Pharmaceuticals & Biomedical, Retail & Web, Finance).
* Excellent analytical and programming skills at various levels (preferably Python) to support data extraction and analysis.
* Experience in MongoDB and SQL databases.
* Experience in using Data visualisation software such as Microsoft Power BI, Tableau.
* Excellent knowledge in Microsoft tools (Excel, Visual Basic, Access, Word, PowerPoint).
* Experience working in Cloud platforms.
* Advanced understanding of statistical methods, machine learning and AI.
* Basic understanding of lithium-ion cell chemistry, design construction and formats. Experience in the design and development within an industrial manufacturing setting, which can be transferred to Lithium-ion batteries.
* Exposure to six sigma training.
* Experience in using Siemens OpCenter.
Personal attributes:
* Possess a positive can-do attitude with the willingness to work cross functionally.
* Thrives to learn and is flexible and adaptable in approach.
* Work proactively to gather data and be inquisitive to maximise insights.
* Be customer focused in their delivery.
* Be persistent is troubleshooting and debugging issues.
* Be open minded with the ability to manage various stakeholder requirements and expectations on data management (voice of customer).
* Strive to continuously improve tools and how the company manages data.
* Possess the ability to prioritise workload.
* Be an excellent communicator in explaining complex ideas and outcomes to various levels (senior management, technical, non-technical) as part of their day-to-day activity and at meetings.
* Possess a strong attention to detail – data driven, diligent and thorough in approach.
* An effective team player who supports team members.
* Resilient and enthusiastic, an individual able to deliver results under pressure.
* Be results driven with the ability to deliver outcomes in a highly demanding environment.
* An individual who is passionate about what they do and is naturally inclined to share knowledge and ideas to the wider team.
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