Schaeffler is a dynamic global technology company and its success has been a result of its entrepreneurial spirit and long history of private ownership. Does that sound interesting to you? As a partner to all of the major automobile manufacturers, as well as key players in the aerospace and industrial sectors, we offer you many development opportunities. 

 

Your Key Responsibilities Preparation of a Master's thesis as part of your studies on the topic of Implementing a Machine Learning Model for demand forecasting in Supply Chain Management Conduct a comprehensive literature review to identify the latest developments in machine learning algorithms for demand forecasting in supply chain management.  Identify scenarios where machine learning and deep learning are particularly suitable for demand forecasting.  Contrast these scenarios with those in which classical models such as statistics, regression and time series analysis are better suited to achieve better forecasting results.  Identify five specific algorithms including relevant variables (features) that are best suited for the data scenario at Schaeffler Vehicle Lifetime Solutions. Based on the results of the literature review, implement the two most promising algorithms with the features identified in the literature on a subset of the data. Compare the forecasting performance of the implemented algorithms with the forecasting performance of two currently implemented forecasting systems.  Based on the results, provide recommendations for further development.   Your Qualifications Studies in Mathematics, Natural Sciences, Informatics, Industrial Engineering, Engineering Sciences, Computer Science, or a comparable field of study. Knowledge and experience with Python and SQL. Basic knowledge in Machine Learning and Time Series Analysis. Preferably experience in the field of Supply Chain Management or E-Commerce. Good written and spoken German and English skills. Good communication and organizational skills Independent, structured, and responsible working approach.

As a global company with employees around the world, it is important to us that we treat each other with respect and value all ideas and perspectives. By appreciating our differences, we inspire creativity and drive innovation. In this way, we contribute to sustainable value creation for our stakeholders and society as a whole. Together, we advance how the world moves.

 

Exciting assignments and outstanding development opportunities await you because we impact the future with innovation. We look forward to your online application.

 

www.schaeffler.com/careers

 

Your Contact

Schaeffler Vehicle Lifetime Solutions Germany GmbH & Co. KG 

Marc Stotmeister 

+4969271351029 

 

 

Keywords: Student; Thesis; Full-time; Temporary; Data Science Solutions, Machine Learning, Demand Forecasting, Supply Chain Management