Data Scientist (m/f/d)
Technische Universität München (TUM)
74 Heilbronn, Deutschland
Home-Office
3.10.2025
Mehrjährige Berufserfahrung
- Collecting and crawling data from diverse sources (websites, databases, social networks, etc.)
- Preparing and preprocessing datasets, conducting initial analyses for application-oriented projects in optimization, AI, and machine learning.
- Independently identifying, assessing, and evaluating potential data sources to support research initiatives
- Involving one or two following potential application domains of smart manufacturing, market, and mobility, e.g.,
- Manufacturing: Developing advanced optimization and AI models and algorithms in application to manufacturing, such as collaborative systems, Industry 4.0 applications, or circular economy. Managing a project on designing an opensource benchmark manufacturing databank and simulation environment, aiming to integrate classical scheduling problems (e.g., flexible job shop, resource-constrained project scheduling) with real-world applications and case studies
- Marketing: Setting up simulation environments for consumer behavior research applications (e.g., customization tools); Design, implement, and optimize complex online surveys using client-side scripting and platform custom code to build interactive modules, conditional logic, dynamic content, and data integrations; advanced user generated data and digital content analysis
- Transportation: Developing advanced machine learning and data analytics models under the simulation or real-world applications of smart transportation, such as traffic signal control, traffic demand prediction, congestion management and causal analysis, emerging new mobilities.
- Contributing to the development of influential benchmark datasets that enhance algorithmic research.
- Managing data storage, documentation, anonymization, and publication
- Performing data analysis and visualization using cutting-edge scientific methods
- Writing data documentation and summary reports for internal and external use
- Assisting in preparing teaching materials on courses in machine learning, optimization, data management, data analysis, and data visualization.
Berufserfahrung
- Mehrjährige Berufserfahrung