Data Science Master's Program

Program director


Christian Fons-Rosen

UPF and Barcelona GSE

Omiros Papaspiliopoulos

ICREA-UPF and Barcelona GSE

The digital revolution brings with it an explosion of data that carries significant potential value for businesses, science, and society.

As data becomes easily available as never before, so too does its volume grow, and extracting useful quantitative insights becomes more and more challenging. 

The Barcelona GSE Master in Data Science prepares its graduates to design and build data-driven systems for decision-making in the private or public sector, offering a thorough training in predictive, descriptive, and prescriptive analytics.

The curriculum will guide students from modeling and theory to computational practice and cutting edge tools, teaching skills that are in growing global demand. 

Data Science students will be armed with a solid knowledge of statistical and machine learning methods, optimization and computing, and the ability to spot, assess, and seize the opportunity of data-driven value creation.

Students will learn how to apply classroom examples using real data and answering concrete business questions from the perspectives of different industries. Through an independent master's project and the opportunity for industrial practicum work conducted with local businesses, students can have the opportunity to solve actual analytics problems hands-on.

Our courses are taught by leading academics and researchers in the fields of Economics, Operations, and Statistics, as well as experienced professionals from the analytics industry.

The program also invites guest speakers and entrepreneurs working at the frontiers of the Data Science.

What skills and knowledge will I acquire in this master's program?
  • Expertise in modern computational, high-dimensional and simulation-based Statistics and Machine Learning
  • Solid evaluation of the opportunities of data-driven value creation within companies and organizations
  • Ability to apply appropriate statistical methodologies and optimization techniques in solving complex problems
  • Innovation with database management systems and distributed processing in a cloud computing environment
  • Experience analyzing Big Data from the Internet of Things (industrial sensor data), the Internet of People (social and location data), and business transaction data
  • Effective communication of data analysis results through presentation and aesthetic charting skills
Who will benefit from this program?
  • Graduates in Economics or Business with a solid economics grounding, and keen interest in quantitative methods
  • Graduates in Computer Science, Engineering, Mathematics, Physics, or Statistics with the ambition to work on real-world problems and data
  • Programming professionals looking to acquire analytical and quantitative tools to leverage their experience
  • Aspiring PhD students looking for rigorous training in quantitative and analytical methods
Who hires graduates of this program?
  • Consumer Goods, E-commerce, Entertainment, Pharmaceutical, and Telecommunications Industries
  • Logistics and Transportation Industries
  • Finance and Insurance Industry
  • Consulting and Research Organizations
  • Banking and Public Institutions

Examples of placements from the first class of Data Science graduates (Class of 2015):

  • Accenture
  • Bluecap Management Consulting
  • Kernel Analytics
  • King
  • Schibsted Media Group
  • Vueling

Download all results for Data Science 2015

Where can I read the Data Science student blog?

Barcelona GSE Data Scientists is a blog written by our students about program activities and current topics in Data Science.


Check out some of the posts:



Program schedule: 

The Data Science program is organized around four pillars:

  • Statistics and Machine Learning
  • Optimization and Operational Research
  • Data Warehousing, Business Intelligence, and Big Data Analytics
  • Economics, Finance, and Policy-Making

In September, students are required to take three brush-up courses. Students who can provide evidence of sufficient past coursework may be exempt:

Fall Term (September - December)

Course Title Credits Professor(s)
All courses are mandatory.
Statistical Modelling and Inference 6 Omiros Papaspiliopoulos
Deterministic Models and Optimization 6 Marc Noy
Data Warehousing and Business Intelligence 3 Guglielmo Bartolozzi
Computing Lab 3 Christian Brownlees
Economics for the Era of Big Data 3 Christian Fons-Rosen (coordinator)

Winter Term (January - March)

Course Title Credits Professor(s)
Advanced Computational Methods 3 Hrvoje Stojic
Financial Econometrics 6 Christian Brownlees
Machine Learning 6 Gábor Lugosi
Electives - Select 0, 3, or 6 credits:
Data Visualization 3 Michael Greenacre
Ioannis Arapakis
Stochastic Models and Optimization 3 Mihalis Markakis
Quantitative and Statistical Methods II * 6 Stephan Litschig
Joan Llull

* Course joint with Economics of Public Policy master program. Requires some prerequisite knowledge and authorization of the program director. Availability depending on sufficient demand.

Spring Term (April - June)

Course Title Credits Professor(s)
Master project 6  
Electives - Select 0, 3, or 6 credits:
Note: This list is not exhaustive. Other electives will be available.
Industrial Practicum
Complements the master project with credits if student is placed in company working full-time
6 Subject to availability and selection process
Big Data Analytics I 3 Pau Agulló
Big Data Analytics II 3 Alexandros Karatzoglou
Matthew Eric Basset
Argimiro Arratia
Social and Economic Networks 6 Joan de Martí
Text Mining for Social Sciences 3 Stephen Hansen
Continuous-Time Finance ** 6 Eulàlia Nualart
Digital Market Design 3 Sandro Shelegia
Public Policy in the European Union ** 3 Juan Francisco Jimeno
Albert Bravo-Biosca
Quantitative Methods of Market Regulation ** 3 Albert Banal

** Requires some prerequisite knowledge and authorization of the program director. Availability depending on sufficient demand.

Master degree awarded

Upon successful completion of the program, students will receive a Master Degree in Data Science awarded jointly by Universitat Autònoma de Barcelona (UAB) and Universitat Pompeu Fabra (UPF).

All Barcelona GSE master degrees have been recognized by the Catalan and Spanish Education authorities within the framework of the Bologna Process (in Spanish, “Master Universitario o Master Oficial”). Indicadors de qualitat