This English-language MSc is offered through the university’s International Study Programme (ISP Page Flow) and prepares students to analyse and monitor the performance of both public and private organisations using quantitative methods. The curriculum combines business and management knowledge with data management and advanced analytics so graduates can deliver data-driven information to support strategic, tactical and operational decisions. Particular emphases are on solving complex problems in supply chain management and financial management.
The degree is interdisciplinary and rests on a strong foundation in data analysis, quantitative modelling and algorithmic methods. It is taught in cooperation with the School of Mathematics and Computer Science, making it suitable both for direct entry into demanding roles across the private and public sectors worldwide and for continuation to doctoral research. International applicants should be prepared for mathematically and computationally rigorous coursework.
Prerequisites and key facts
The programme blends compulsory elective coursework in Quantitative Methods and in Methods of Computer Science with a wider selection of approved ORBA courses that you can pick according to your interests. In addition to taught modules, you must take designated compulsory elective seminars and complete a scientific project. The master’s programme is concluded by a written thesis and an accompanying thesis seminar.
Classroom teaching totals roughly 20 hours per week and is complemented by at least 20 hours of independent study, so expect a full-time workload of around 40 hours weekly. Teaching formats include lectures for introducing concepts, tutorials for discussion and skills practice, and seminars where you apply theories and methods to project work. The scientific project requires an academic paper and a final presentation.
Graduates will develop strong quantitative and computational skills closely tied to mathematics and computer science, preparing them to model, analyse and solve complex business problems using scientific methods. You will learn to work independently on research topics—designing studies, applying rigorous methods, producing written academic work and presenting results. Because of the programme’s technical emphasis, solid undergraduate grounding in programming languages and advanced mathematical techniques is essential for success.
Detailed module descriptions are provided in a downloadable PDF for students who want full syllabi and assessment details.
Requirements (concise)
This programme requires a completed Bachelor's degree (or equivalent) in a related field and evaluates applicants on academic background, quantitative skills, and motivation. Degrees must come from a recognised university and meet the programme’s subject-area requirements (economics, business administration and related quantitative modules such as mathematics, statistics, econometrics). Prior exposure to computer science and programming, plus relevant work experience, strengthen an application.
Admission is competitive and places are limited (NC — numerus clausus). Shortlisted applicants will be invited to an interview (held in August) and final offers are made after a ranking-based selection process. For detailed information on acceptable degrees, the standardised Letter of Motivation form, and recognised English tests/levels, consult the programme’s website and timeline.
Admission requirements (summary)
For exact details, acceptable documentation, and timeline dates, refer to the ORBA programme web pages and admission timeline.
Winter Semester (International)
15 June 2026
Graduates are prepared for quantitatively demanding roles in both the private and public sectors worldwide, such as operations analyst, business/data analyst, supply chain manager, risk or financial analyst, and analytics consultant. The programme’s strong emphasis on algorithms, modelling and data management also makes it a good foundation for careers in technology firms and consultancies.
For students interested in academia, the curriculum and research project components provide preparation for doctoral studies. The faculty and university career services, together with active student organisations, support students in finding internships and placement opportunities to gain practical experience during the programme.
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