Data Science for Society and Business
The Master of Science in Data Science for Society and Business at Constructor University in Bremen is an international graduate program designed for students seeking to combine data-driven analysis with insights from the social and business sciences. This full-time, interdisciplinary degree integrates academic excellence with practical relevance, preparing students to address complex challenges in modern organizations and digital societies. Students gain advanced knowledge in data analytics, computational modeling, and statistical inference, developing essential skills for research and professional environments. The program is structured across four semesters and admits students exclusively in the winter semester.
Located in Bremen, a leading hub for innovation and technology, this master’s program emphasizes both analytical rigor and real-world application. With a strong focus on interdisciplinary collaboration and hands-on experience, students engage in projects that bridge data science, economics, sociology, and business. The program reflects Constructor University’s commitment to combining scientific depth with practical impact, making it an excellent choice for those aiming to apply data science in social, economic, and organizational contexts.
Key information
Key Facts
- Degree: Master of Science (M.Sc.)
- Standard period of study: 4 semesters
- Location: Bremen
- Study Type: Graduate (full-time, international)
- Admission semester: Winter semester only
- Area of study: Data Science, Business Analytics, Social Science, Computational Methods
- Admission modus: Selection procedure / qualifying examination
Program Structure
Semester 1 – Foundations of Data Science and Society
- Introduction to Data Science
- Statistical Modeling and Analysis
- Fundamentals of Social and Business Research
- Programming and Data Management
Semester 2 – Advanced Data Analysis and Applications
- Machine Learning and Predictive Analytics
- Big Data and Cloud Computing
- Data Visualization and Communication
- Interdisciplinary Seminar: Data and Society
Semester 3 – Specialization and Applied Research
- Advanced Topics in Computational Social Science
- Business Intelligence and Decision Making
- Elective Track (choose one): Computer Science / Bioinformatics / Geo-Informatics / Business & Supply Chain Engineering
- Research Project I
Semester 4 – Master’s Thesis and Professional Development
- Research Project II
- Master’s Thesis
- Presentation and Portfolio Development
Career Opportunities
Graduates of this program are equipped for diverse careers in data-driven fields such as data analysis, machine learning, business intelligence, and computational social science. They can work in technology companies, consulting firms, research institutes, and international organizations. The interdisciplinary skill set also opens doors to leadership positions in business strategy, policy research, and innovation management.
Why Choose This Program
Choosing the Master of Science in Data Science for Society and Business means joining a forward-looking program that integrates social understanding with technical expertise. Students benefit from world-class faculty, an international learning environment, and strong links to industry partners.
The program’s distinctive blend of social science and computational training provides graduates with a competitive edge in a global job market increasingly shaped by data. Constructor University’s focus on interdisciplinary collaboration and real-world problem-solving ensures that students are not only data experts but also strategic thinkers capable of driving innovation and change.
Contact Information
Constructor University – Admission Office
Campus Ring 1
28759 Bremen, Germany
Tel: +49 421 200-4200
Email: admission@constructor.university
Programme Contact
Constructor University Bremen
Campus Ring 1
28759 Bremen, Germany
Email: graduateadmission@constructor.university
International Office
Campus Ring 1
28759 Bremen, Germany
Tel: +49 421 200 4315
Email: international@constructor.university
