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Data Scientist (m/f/d)
Heilbronn, Remote
Aktualität: 21.06.2025

Anzeigeninhalt:

21.06.2025, Technische Universität München (TUM)
Heilbronn, Remote
Data Scientist (m/f/d)
Aufgaben:
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 Designing and setting up simulation environments for modern manufacturing systems, integrating classical scheduling problems (e.g., flexible job shop, resource-constrained project scheduling) with real-world applications and case studies. Setting up simulation environments for consumer behavior research applications (e.g., customization tools). Contributing to the development of influential benchmark datasets that enhance algorithmic research. Assisting in setting up and running experiments, including using platforms (e.g., Qualtrics) to design and administer surveys. Adjusting and customizing questionnaires, incorporating programming languages (e.g., JavaScript) to tailor the experimental setup to specific research needs. 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.
Qualifikationen:
We are looking for a proficient specialist in coding, data crawling, simulation, data mining, and data visualization. The ideal candidate combines strong foundational knowledge in core data science disciplines-such as statistics, modeling, and optimization-with a keen interest in understanding contexts, causal relationships, and complex dynamics across various management domains, including manufacturing, marketing, and transportation. A completed academic degree at master's level in management/business administration, economics, mathematics, information systems, informatics, business engineering, or a related field A strong interest in areas related to management and business Experience in extracting, cleaning and analyzing data (e.g. business research databases, websites) using scientific methods Experience in programming and developing software packages (e.g., C++, Python, Julia) Experience in conceptualization, publishing, and documentation of (opensource) code environments Experience in developing simulation environments is advantageous Knowledge in optimization modeling. Basic knowledge in scheduling is advantageous Experience in data storage and management Strong communication skills in English Very good organizational skills Enthusiasm for algorithm design and innovative empirical research Speaking German is an asset, but not required

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