Data Scientist Automotive EMEA (m/f/d)
- Speyer, Germany
At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.
The CoE Digital EMEA team is part of the Continuous Improvement EMEA Team, focusing on waste elimination and efficiency improvements in all its aspects, with a significant contribution on the overall financial performance of Automotive EMEA.
The Continuous Improvement EMEA team reports to Operations Automotive EMEA.
By providing new generation digital solutions to our Operational teams across EMEA, our team creates full transparency and speed in the ongoing digital & lean transformation(s), which will enable all involved functions to leverage data to develop business insights and roadmap updates based upon clearly arranged and understandable data.
Due to the extended scope, focusing also on the connecting processes from Supplier(s) to Manufacturing ending at the Customer(s) (internal and external) we will function as 'the' differentiator for our Company.
This new position 'Data Scientist Automotive EMEA' will report to the Manager CoE Digital EMEA.
Tasks & Responsibilities:
- Lead projects and work together with our Automotive EMEA Operations plants, internal (IT, TEIS, Corporate Technology, CoE, SC, ..) and external partners in the area of Digital Factory (Applications, ML, AI, DL), aligned with Operations Automotive EMEA Strategy.
- Lead Digital Factory improvement projects (Enhancements) of existing applications together with internal / external supplier and customers (project management) until the level of RTD (Ready To Deploy)
- Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems
- Identify and interpret data sources, manage large amounts of data, merge data sources together, ensure consistency of data-sets, create visualizations to aid in understanding data
- Develop, Validate and Deploy (including Training and Coaching of the users) until the level of RTD (Ready To Deploy), Digital Factory Applications, ML models, contributing to waste elimination and efficiency improvements within all Operations functions (Manufacturing, Quality, SC, LOG, ...), this together with our internal and external partners.
What your background should look like:
Expected Experience, Skills & Behavior:
- Bachelor or Master in Data Science or IT
- Development experience in programming languages R, Python,..
- Experience in technologies like, Jupyter Notebooks, Numpy, Pandas, Seaborn, Scikit-learn, PyTorch and TensorFlow.
- Good understanding of a technology driven manufacturing company.
- Knowledge of the core manufacturing technologies: Stamping, Plating, Assembly, Molding.
- Experienced with data visualization tools like PowerBi, Tableau, ThingWorx,..
- Good applied statistics skills, such as distributions, statistical testing, regression, etc
- Excellent pattern recognition and predictive modelling skills.
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, neural networks and deep learning etc.
- Exposure to recent developments in Deep Learning domain.
- Database skills, on-premises and cloud based.
- Experience in AWS is an advantage, functional knowledge of AWS platforms such as Sagemaker, S3, and RedShift.
- Excellent presentation skills in both spoken and written English.
- The ability to translate, explain and bring, complex data science topics to an easy understandable level, speeding up acceptance level in general
- Team player with a solution focused problem solving mentality.
- Change agent with high Execution level, including training and coaching talents.
- Passioned about the combination Technology, Data, Analytics and Statistics with link to Quality, Product and Process Engineering
- Inspired by and searching actively for new technologies and methods.
Managing and Measuring Work
Building Effective Teams
Values: Integrity, Accountability,Teamwork, Innovation
SET : Strategy, Execution, Talent (for managers)
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