Master Thesis Data Science Solutions VLS Germany (m/f/d)

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.