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.
The Vehicle Lifetime Solutions division is responsible for Schaeffler's global spare parts business. With innovative strength, technical expertise, and the highest product quality, Schaeffler Vehicle Lifetime Solutions is the trend-setting provider of repair solutions and services for internal combustion engines, hybrids, and electric vehicles and prepares the independent aftermarket for the technologies of tomorrow.
Your Key Responsibilities
• Preparation of a master's thesis as part of your studies on the topic of implementing a Machine Learning/Deep Learning/Foundational model for demand forecasting in supply chain management
• Conducting a comprehensive literature review (based on scientific literature and data from ML competitions) to identify recent developments in the areas of machine learning, deep learning, foundational/transformer algorithms, and specialized architectures for demand forecasting in supply chain management
• Identification of feature engineering approaches to optimize model performance based on the literature review
• Implementation of the five most promising feature sets with the currently implemented model, based on the results of the literature review
• Comparison of the forecast performance of the implemented algorithms with the forecast performance of the currently implemented forecasting system
• Investigation of scenarios where classical statistical methods yield better performance than more sophisticated methodologies
• Providing recommendations for further development based on the results
• Outlining avenues for further research in this domain
Your Qualifications
• Studies in Data Science, Mathematics, Natural Sciences, Business Informatics, Industrial Engineering, or a comparable course of study
• Very good knowledge and experience with Python and SQL
• Knowledge of Machine Learning and Time Series Analysis
• Preferably experience in the areas of Supply Chain Management or e-commerce
• Good German and English skills, both spoken and written
• Good communication and organizational skills along with a self-reliant, structured, and responsible work approach
Our Offering
* Flexible working time models and attractive remuneration
* A wide range of further personal development opportunities via the Schaeffler Academy
* Rewarding your wealth of ideas, e.g., within the framework of the Schaeffler Awards and operational idea management
* Health and sports offerings, e.g., through the Schaeffler Health Coach app
* Accumulation of an additional old-age pension as part of the company pension scheme
* Many other employee benefits, among others within the scope of corporate benefits
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.
This position is located in Frankfurt. 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
Alessa Robl
Keywords: Students; Thesis; Full-Time; Limited; Administration, Services & Support;