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Data Quality
3 months ago
We’re re-examining our vehicles and what a vehicle means in the emerging world of automation, connectedness, electrification and the shared economy. New ideas, new technology, and new approaches to mobility are our business. Join a team of next generation thinkers.
WHAT TO EXPECT
Be a part of the JLR team, testing the next generation of electrified propulsion systems for JLR products. We are at the forefront of development in hybrid and full electric powertrains, aiming to deliver electrifying performance and peerless refinement. We are looking for individuals who are eager to learn about our data management and validation and can bring their passion and experience to our growing team.
You will work across Electric Machine, Electric Drive Unit (EDU), Inverter, Cell, Battery, Power in loop (PiL) and Vehicle in Loop (ViL) test beds covering. The person in data validation and management role will be responsible to provide timely, accurate, secured and accessible test data for wider engineering group to enable efficient engineering decisions.
You will be the working towards to become the Subject Matter Expert for data management and validation and deliver a training package to develop others in order to improve the data quality produced by the team.
Key Accountabilities and Responsibilities
Be responsible in data sources and data acquisition, data quality validation, data pipeline, data storage and data visualisation for physical test environment. Delivering data quality reviews in order to support programme targets and prove out chosen technologies. Develop calculations, parameterisation, regulations and process of in-house data tool development. Research, communicate and implement best practice data quality methods and improve test field efficiency. Investigate best ways of working to make full use of equipment capability in order to improve data quality and to continually encourage a growth mind-set across the team.WHAT YOU’LL NEED
Previous experience in designing applications in different programming languages (preferably Python). Building of data systems & pipelines, data validation and management in cloud platforms (AWS, Google Cloud). Data analysis skills, including hypothesis testing, uncertainty analysis, and process variation. The ability to work closely with engineering stakeholders influence analysis techniques to inform engineering decisions. Develop Key Performance Indicators (KPI) and ability to carry out graphical data presentation and deliver written reports and technical presentations.