Working Student Data Science - Data-Driven Scheduling Optimization | Werkstudent Data Science - Data-Driven Scheduling Optimization (m/w/d)
TÜV SÜD AG
Job Summary
As a Working Student in Data Science, you will play a key role in optimizing task and route planning through advanced analytical methods. Your day-to-day responsibilities will involve implementing mathematical optimization procedures, machine learning algorithms, and artificial intelligence models, with a specific focus on forecasting. You will work within an agile, interdisciplinary team alongside other data scientists and software developers to process and visualize results while maintaining comprehensive documentation. This position is particularly attractive for students looking to apply theoretical knowledge to real-world industrial challenges within a globally recognized safety and sustainability organization. The role offers flexibility with a workload of 10 to 20 hours per week, providing a perfect balance between academic studies and professional development in a cutting-edge technical environment.
Required Skills
Education
Current enrollment in a relevant Master's degree program (e.g., Mathematics, Business Informatics, Data Science, or Operations Research).
Experience
- Initial practical experience in the field of Data Science or mathematical optimization is preferred
- Experience working within agile, interdisciplinary project teams
- Experience in creating and maintaining technical documentation
- Proficiency in data processing and visualization
Languages
Additional
- Availability for at least 10 hours per week on-site, with a maximum of 20 hours per week possible.
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