Master of Science in Statistics and Data Science

In the Master's degree program in Statistics and Data Science students are introduced to important models and methods from Probability Theory, Statistics, Financial Mathematics, Actuarial Science, and study aspects of Computer Science that are relevant for Data Science. The methods of Statistics and Data Science are applied in diverse fields and are considered a key technology for scientific research. The students of the Master's degree program get acquainted with recent research in these fields and are guided to work independently on a scientific project.

Master in Statistics and Data Science
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"Anyone can use a statistical method. Understanding it is what sets you apart."

Statistics is a scientific discipline concerned with drawing inference from experimental or empirical data and quantifying uncertainty in estimates and predictions. Its methods are grounded in probability theory and formulated rigorously as mathematical models, allowing their properties to be studied independently of specific applications.

Data collection and modelling are also central. Increasing digitisation and the growing volume of data present new challenges, addressed by methods commonly grouped under data science.

The Master’s programme in Statistics and Data Science introduces core concepts from statistics, probability theory, financial mathematics and actuarial science, alongside computational methods for analysing large datasets. Students engage with current research and complete an independent scientific project (Master’s thesis).



Basic information
Degree:

Master of Science in Statistics and Data Science, University of Bern (MSc)
Number of credits: 90 ECTS credits
Degree programs:
  • Mono 90 ECTS credits

 
Option for students pursuing other degrees:

  • Minor 30 ECTS credits
Duration: 3 semesters
Language: English
Beginning of studies: Fall or spring semester

Details of program

The program places a strong emphasis on core models and methods from Probability Theory, Statistics, Financial Mathematics, and Actuarial Science, all grounded in rigorous mathematical foundations. Applicants are expected to demonstrate solid mathematical knowledge during the interview process. Students are also introduced to the important methods of Computer Science relevant to Data Science, and may also take courses from the Master program in Mathematics. The students get acquainted with recent research in these fields and are guided to work on a scientific project (Master thesis).

The Institute of Mathematical Statistics and Actuarial Science offers part-time positions as teaching or consulting assistants to very strong students who are also fluent in German.

For more details regarding the program see, the scheme of program document here.

For commonly asked questions, see here.

Structure of program

The Master in Statistics and Data Science (as major) corresponds to 90 ECTS points. It consists of the Master module of 60 ECTS and a Master thesis corresponding to 30 ECTS. The study time is 3 semesters.

The courses in this program are held in English.

For a list of current courses offered by the institute, see here.

For information regarding courses offered currently, see here.

Sem. Master in Statistics and Data Science (Major, 90 ECTS) according to the plan of studies from December 13th, 2018
7 Master module, 60 ECTS: Lectures of the Master program in the areas Statistics (ST), Probability Theory (WT), Finance and Insurance (FV), Mathematics (MA) and Computer Science (IN), and at least one seminar. At least 20 ECTS have to be attained in Statistics, and at least 10 ECTS in two of the other areas.
8 Master thesis, 30 ECTS
9

Master’s thesis

For the supervision of MSc theses, all full-time lecturers of the Department of Mathematics and Statistics are eligible. One can not claim supervision by a particular person.

Supervision of a MSc thesis by an external person requires approval by the Director of Studies in Statistics. Probably he/she appoints a co-supervisor from the department.

For a selection of previous thesis titles by previous Master’s students, see here.

Deadlines

Exam dates

The oral or written exams generally take place two weeks before the start of the following semester. All students have to register for the exams through KSL, where the dates for the registration are fixed. Until about two weeks before the exam, there is the possibility to cancel the registration.

Special dates for exams for exchange students are usually in the last week of the semester. Please consult the lecturer in charge for further information.

Tentative dates of admission interviews

- January 12th

- April 15th

- June 3rd

- August 19th

- November 11th

Requirements

Individual academic requirements

The following academic qualification is required for admission to the master’s degree program in Statistics and Data Science (mono):

a) Bachelor's degree from a recognized Swiss university in one of the branch of studies Mathematics or Computer Science, with a sufficient share from the field of Stochastics,
b)

Bachelor's degree from a recognized Swiss university in a different branch of studies with at least 60 ECTS credits in one of the branch of studies Mathematics or Computer Science, with a sufficient share from the field of Stochastics, provided that the master's degree can be successfully completed with an additional maximum 60 ECTS credits (admission requirements which must be fulfilled in order to complete the master's degree program),
c) Bachelor's degree from a recognized international university with equivalent qualifications, with a sufficient share from the field of Stochastics, provided that the master's degree can be successfully completed with an additional maximum 60 ECTS credits (admission requirements which must be fulfilled in order to complete the master's degree program).

Please consult the admission requirements for the minor as presented in the plan of studies.

The degree used for assessment purposes may not be more than ten years old.

The admission is subject to a standardized interview with the director of studies (Art. 15). The director of studies applies to the study committee for admission to the Master's program.

 
For questions regarding application and admission, please contact the Admissions Office.

Application and admission

Current UniBE students Mathematics and Computer Science

Apply for a change to the M Sc in Statistics and Data Science, Universität Bern by self-service as part of the re-registration for the next semester.
Registration for the standardized interview (document in German)
For questions about admission to the Specialized Master's in Statistics and Data Science: master.stat@unibe.ch
Renewal of semester registration → Self-service
Assessment
Procedure and timing of the renewal of semester registration

Application with a Swiss degree

Online application
Assessment and registration for the standardized interview (document in German)
Steps from application to registration

Application with an international degree

Online application
CHECKLIST - documents for your application / important information
Steps from application to registration

 
For questions regarding application and admission, please contact the Admissions Office.

Graduation

As soon as the requirements set by the study regulations are fulfilled, you can apply for a formal completion of your studies through the Deans office. The information about the completion process you can find here.

After your Master's

There is a large demand for skilled statisticians and actuaries. Career prospects are excellent. Statisticians and data scientists are employed in insurance companies or banks, in public administration, in transport companies, as well as in the medical and private sectors. Increasingly, graduates also work in artificial intelligence (AI), machine learning, and data-driven decision-making, developing predictive models and intelligent systems across a wide range of industries.

After completing your studies (Master’s or PhD), there are various options for further qualifications, such as the postgraduate program in actuarial science offered by the Swiss Association of Actuaries (SAV). Graduates may also specialise further in areas such as AI, deep learning, or big data engineering, or pursue research and development roles in academia or industry.