Rapidly growing amounts of data as well as recent advances in data analytics allow for completely new opportunities to solve hard real-world problems in a data-driven manner. This is impressively demonstrated by the latest achievements, e.g., in genome analysis, image recognition, self-driving cars, or in situation detection in crisis events. Data Science is an interdisciplinary field at the interface between Computer Science, Statistics, and Business Informatics dealing with huge amounts of multivariate, heterogeneous data, which needs to be analyzed and interpreted in order to draw adequate decisions. Harvard Business Review has called Data Science "The Sexiest Job of the 21st Century", while McKinsey & Company are estimating a global excess demand of 1.5 million new data scientists in coming years.

The multi-faceted and complex nature of Data Science problems requires interdisciplinary teams to master them. To educate such teams, JKU offers three entry points into the world of Data Science by providing Data Science as a specialization (focus area) in the Master's programs Computer Science, Statistics, and Business Informatics.

This truly interdisciplinary approach offers undergraduates with different backgrounds and interests a tailored education in data science. All three programs are fully taught in English. For information about admission, see the links above or JKU's general admission regulations for master students.


Graduates of one of the JKU Data Science foci are highly sought-after experts

  • with a high job placement rate in a wide range of organisations and enterprises such as universities and research institutions, pharmaceutical industry, clinical or medical facilities, public administration and NGOs, production industry, banks and insurance companies,
  • with key responsibilities for statistical modelling, prediction and forecasting, risk assessment and management, fraud detection, customer/behavior modeling and customer relationship management, analysis and improvement of business and production processes, management of enterprise strategy.