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Job Location | Great Abington |
Education | Not Mentioned |
Salary | Competitive salary |
Industry | Not Mentioned |
Functional Area | Not Mentioned |
Job Type | Permanent , full-time |
Kenton Black Scientific Division is collaborating with a multinational company that operates in the Personal Care Industry. They are leading the way in understanding the science of hair, and their product portfolio include electronic goods and formulatedproducts. The R&D labs are unique in combining physicists, material scientists, product designers. We are looking for Data Scientist to join the team.The role will involve capturing, extracting, analysing and reporting product, user, and hair performance data using scientific methods and data analysis techniques to drive high performance products in R&D and NPD, and identify future opportunities for theinnovation pipeline. The Role: Early-stage development of hair, user and product sensing technologies to help define the future of breakthrough product pipeline, including IoT or connected & smart devices Support the testing of new technology, utilising physics to define the future of electrical hair styling technologies Work with internal matrix resources and external consultants through early phases of developing and creating proof of principle prototypes to showcase holistic feasibility Work with the science team to understand latest research in the hair-care and beauty fieldThe Candidate: Honours degree educated in Physical Sciences, Engineering or similar discipline with demonstrable experience in data science and proven track record of integrating data from multiple sources A strong communicator with the ability to convey complex information in a simple manner Prior experience / knowledge of some of the following: handling big data, predictive modelling, statistics, machine learning, AI, IoT, signal and image processing, database management, DoE and lab testing Python programming experience and related data science libraries (such as Pandas, Numpy, Tensorflow/Keras, openCV) Experience working with cloud technologies e.g., Microsoft Azure, AWS would be desirable
Keyskills :
Data Scientist Physicist Predictive Modelling Statistics Machine Learning AI Python Cloud Technologies