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Data Science Engineer
4 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
We are looking for Data Science Engineers, to be based in the Battery Systems Advanced Concepts & Research Pillar, who will be reporting to the Pillar Head. The Data Science Chapter will be responsible for implementing Data Science solutions to meet component functional targets.
The industry is growing quickly at a time when the technology is changing rapidly which poses a number of challenges for JLR. The technology is changing at a faster rate compared to our normal maturation timelines. So, to manage this, we must look forward and identify the right technologies that we need to invest in and determine how we grow as a team to accommodate and deliver this.
The battery team is one of the fastest growing teams in the JLR business with main focus to respond to the increasing mix of BEV vehicles in our cycle plan.
Key Accountabilities and Responsibilities
As a Data Science Engineer, you will develop the Data Science part of the BEV battery technology roadmaps to support JLRs electrification transition.
Develop and consolidate data models based on benchmark testing from device to vehicle level, enhancing our understanding of competitors and the current/latest technology landscape Work alongside our materials science and engineering operations teams to ensure they have the right data at their fingertips to enable then to execute the technology roadmap Work alongside key business stakeholders to ensure we meet our vehicle product needs Support the development of a technology roadmap that takes us to the next generation of battery technologies such as solid state and Data Science-to-car / module-to-car conceptsWHAT YOU’LL NEED
Experience of the multi-physics nature of Data Science within engineering and materials science research and development settings Experience of applying Data Science within the battery manufacturing industry along with knowledge of the BEV Data Science and battery landscape across the worldwide supply base or other OEM manufacturers to allow credible and competitive concepts and strategies to be followed Experience manipulating and transforming electrochemical data from batteries cyclers into standard visualisations and outputs, , HPPC, GITT, charge/discharge curves, EIS data Experience in end-to-end machine learning model development for predictive modelling with machine learning algorithms such as Neural networks, Random Forrest, k-nearest neighbour Proficiency in python and experience Working in Cloud environment such as AWS or Azure along with knowledge of GIT and SQL