Data Scientist (m/f/d)

About us The TUM Campus in Heilbronn is part of the renowned Technical University of Munich, which is one of the best universities in Europe. Top performance in research and teaching, interdisciplinarity and talent promotion are its hallmarks. In addition, it has strong alliances with companies and scientific institutions around the world. TUM is one of the first three universities of excellence in Germany. The TUM School of Management is also the first management school at a technical university in Germany to receive Triple Crown accreditation. Worldwide, only about 80 institutions (about 1%) can boast this distinction. The Heilbronn Data Science Center is a research institution of TUM Campus Heilbronn that uses data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with application-oriented research that unlocks the potential of data through rigorous analysis - advancing solutions in societally relevant domains. Your tasks We are looking for a proficient specialist in coding, data crawling, simulation, machine learning, data mining, and data visualization. The ideal candidate combines strong foundational knowledge in core data science disciplines such as statistics, modeling, optimization, and machine learning with a keen interest in understanding contexts, causal relationships, and complex dynamics across various application domains, including manufacturing, marketing, and transportation. You will be closely involved in the research projects of the professorships within the Unit for Data Science in Management at the Heilbronn Data Science Center and take responsibility for data-related work packages aimed at high-profile publications and societally impactful research. Your responsibilities include: 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. Your profile A completed academic degree at master\'s level in management/business administration, economics, mathematics, information systems, computer science, industrial engineering, business engineering, or a related field A strong interest in areas related to management, business, or AI and machine learning 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 and strong skillsets in one or two of the following: Manufacturing: 1) Knowledge in optimization modeling; 2) Basic knowledge in scheduling is advantageous; 3) Experience in developing simulation environments is advantageous Marketing: 1) digital content analysis; 2) incorporating programming languages to tailor experimental setup is advantageous Transportation and Smart Cities: 1) Spatial-Temporal Deep Learning and AI (PyTorch), 2) Experience with Large Language Model 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 We offer Self-determined work related to interdisciplinary research projects A diverse and inclusive working environment The opportunity to work in a vibrant scientific environment The possibility to partially work from home as well as a modern, well-equipped workplace on the Bildungscampus Heilbronn Access to advanced training opportunities for professional development Full-time position (part-time possible) Application process We look forward to receiving your application documents (letter of motivation, transcripts of records, CV, other certificates) by Oktober, 31.2025, as a single PDF document via e-mail to (contact person: Ms. Elke Kröber) using the subject \"Data Scientist\". In the letter of motivation, please include a brief selfassessment (150 words at most) outlining how your profile aligns with the qualifications we are seeking, as well as how your expertise matches the responsibilities and tasks associated with the position. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. TUM strives to raise the proportion of women in its workforce and explicitly encourages applications from qualified women. Payment will be based on the Collective Agreement for the Civil Service of the Länder (TV-L) up to a classification in pay group 13 with appropriate qualifications. Note on data protection: As part of your application for a position at the Technical University of Munich (TUM), you submit personal data. Please note our data protection information in accordance with Art. 13 of the General Data Protection Regulation (GDPR) on the collection and processing of personal data in the context of your application. By submitting your application, you confirm that you have taken note of TUM\'s data protection information.