This study program belongs to the School of Business, Social & Decision Sciences
Location: On Campus
The 2-year master program Data Science for Society and Business (DSSB) is a highly selective program for students of business and social sciences aiming to become data science experts. The program is also of high interest to students with backgrounds in health and environmental sciences aiming to expand into big data analytics, data-driven and computational social science, based on their strong quantitative background.
During two exciting years, graduates gain cutting edge competences, tools and methods to discuss, model, predict and solve the pressing challenges of digital societies, modern organizations and competitive businesses.
The truly multidisciplinary program combines a broad course offering from multiple social and data science disciplines with 3 elective tracks to allow for individual diversity and further specialization. With a focus on high employability, DSSB graduates are best prepared for quickly growing, global professional and academic career options resulting from digitization.
The master program Data Science for Society and Business study program teaches international students with strong backgrounds in social sciences (e.g. business, economics, demography, media studies, political science, psychology, sociology,) how to make use of rapidly growing digital data resources and new computational tools and methods to potentially solve the challenging interdisciplinary problems in their professional or academic field.
The program may also be interesting for students with a background in humanities, natural or technical science who want to focus on innovative social data analytics and pressing social and business questions emerging from digitization.
Students of the DSSB program thereby benefit from a broad course offering in various social, data and business sciences and the close cooperation with computer sciences, environmental and life sciences.
At the end of the 2-year program DSSB graduates will have expertise in digital contents and data science skills to responsibly and capably solve core problems in future organizations and digital societies.
In addition, the program also promotes individual diversity and specialization. DSSB students can pick and choose course offerings from the 3 elective tracks based on their individual interests and career plans
The Curriculum at a glance
The MSc Data Science for Society and Business program is composed of foundational lectures, specialized modules, interactive seminars, tutorials and applied project work. These lead to a master thesis that can be conducted in close collaboration with research, institutional or industry partners on or even off-campus i.e. at a partner university, a political organization or at a company site. The program takes four semesters (two years). The following table provides an overview of the modular structure of the program. The program is partitioned into five areas (Core, Elective, Methods, Discovery, and Career) and the Master Thesis. All credit points (CP) are ECTS (European Credit Transfer System) credit points. In order to graduate, students need to obtain a total of 120 CPs.
Schematic study scheme
Core area
Core modules describe and analyze the machine-social context, the changes and the challenges new information technologies impose on today’s and future firms, entire economies and societies. They also teach students data science approaches, new models and analytical techniques. Hence, we aim at three units consisting of two 5 CP modules for research on digitization and societies (10 CP), digital transformation in business (10 CP), and data science and artificial intelligence concepts (10 CP).
Methods area
Methods courses are key in data science. Programming skills, innovative, dynamic models and experimental methods as well as most up-to-date software lay the groundwork for understanding, replicating and contributing to research.
Discovery area
Discovery modules immerse students into diverse applications. Faculty from different disciplines introduce to up-to-date data science applications. Invited experts from business, public administration and other organizations reveal their digital data needs and solutions. These diverse experiences and insights lead to innovative experimentation in a data science lab and culminate in an individual capstone project in which students bring their theoretical and practical expertise together to creatively answer pressing social and data science problems, i.e. in health education, social media marketing, robotics, data security or digital government. Students who prefer to complete an internship with a company, or public organization can exchange the capstone project, and two of the mandatory elective career modules for this off-campus learning experience.
Career area
Modules in the career area aim at broadening the intellectual skills of students and boost their employability. Language modules and seminars on ethical and legal questions help to understand people with other cultural backgrounds and to understand normative concerns about the digitalization of our societies. Targeted modules on communication and career skills directly support students to exchange and function well in professional environments. Students who prefer to complete an internship with a company, or public organization can exchange the capstone project, and two of the mandatory elective career modules for this off-campus learning experience.
Elective area
Electives allow students to expand and connect their expertise with other subjects. Courses in business, computer science, criminology, spatial sciences, public health and supply chain management also allow specialization.
The Data Science for Society and Business graduate program attracts students with diverse career goals, backgrounds and prior work experience.
Students can choose to strengthen their knowledge by focusing in one of 3 different areas:
These are recommended focus tracks. Students may however choose combination of the non-mandatory courses.
All study programs at Constructor University are accredited by the German Accreditation Council, guaranteeing adherence to high academic quality and international standards. This accreditation confirms that each program meets formal and subject-related criteria in terms of content, structure, and intended learning outcomes.
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Cost of attendance 2025 / 2026
The direct costs of attendance include tuition, room and board, and fees, as outlined below.
The MSc Data Science for Society and Business (DSSB) graduate program is a highly selective program for students who have completed their BA / BSc in the social sciences (e.g. business, economics, political science, psychology, sociology,) who want to become a data scientist with an interest in business and social science research questions.
We are also open to accept students from the humanities and natural science (e.g. history, health or other neuro sciences with a quantitative orientation).
DSSB is a truly interdisciplinary program that combines a broad course offering from diverse social and non-social science disciplines with elective tracks for individual diversity and specialization.
By combining on- and off-line learning tools in core and method courses, students with diverse cultural and knowledge backgrounds and individual needs are quickly integrated. Remedial online learning allows to close mathematical or technical knowledge gaps.
Students thereby benefit from a close relation between teachers and students, small classes, shared learning experience and innovative learning environments.
To further gain professional and research practice, students have access to the data science lab, may engage in capstone projects, choose an elective internship or participate in public big data challenges.
This study program is part of the School of Business, Social & Decision Sciences.
When considering the development of our modern global society, individuals are regarded as indivisible biological, psychological, and socially determined beings.
This area includes topics such as social cohesion, state systems, the preservation of social welfare, or the effects of regulatory systems on the individual, such as their impact on human rights. Diversity is thus regarded as a driving force behind development and progress.
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For PhD Degrees please contact:
Dr. Svenja Frischholz
Head of academic advising services
sfrischhol@constructor.university
Phone: +49 421 200 4338
