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Master's Degree in Data Science

Data Science Methodology Program

Learn technical and practical skills to understand how data science works

9 months
full time

19,000€

Face-to-Face

English

60 ECTS

Campus: Ciutadella (UPF)

Program begins in September 2025

Application deadline for 2025-2026, is July 2, 2025

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Master's Degree in Data Science

Applications for 2025-2026 Master´s Degrees are now open!

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Master's Degrees

Master's Degree in Data Science

Data Science Methodology Program

About this Master’s program

This Master’s program focuses on statistical methods, machine learning, and data analysis, emphasizing the application of data-driven decision-making and problem-solving techniques.

Discover what makes this program truly exceptional

1

Leading faculty: Study with strong international researchers in Statistics, Operations Research, and Artificial Intelligence.

2

Small classes: Engage with professors who are published in top research journals in a small class environment.

3

Guest speakers: Gain insights from experts working at the frontiers of Data Science Methods and applications.

4

Go beyond the application of data science methods: Acquire skills to understand your inner workings.

5

Continue with a PhD: Continue on with PhD studies in Data Science at Universitat Pompeu Fabra.

Meet the Program Directors

Program Director

David Rossell

Steering Committee

Christian Brownlees

Steering Committee

Gábor Lugosi

Steering Committee

Lorenzo Cappello

Ready to make a difference? This program is designed for

Students who are passionate about data and learning strong analytical skills. Here’s why it is perfect for you:

You have a background in Economics, Statistics, Physics, Computer Science, Mathematics or Engineering.
You have a strong background in mathematics and statistics.
You have a strong interest in becoming a developer of Data Science methodologies and algorithms.
You are committed to staying up to date with current scientific developments in the field.
You have an interest in the foundations of the field, real-life and large-scale applications.

What skills and knowledge will you learn?

As data becomes larger and more complex, extracting useful quantitative insights is more challenging

Develop methodologies and algorithms:

Learn how to develop new methodologies and algorithms.

Expertise in Statistics and Machine Learning:

Gain expertise in computational, high-dimensional, simulation-based Statistics and Machine Learning.

Develop a research attitude:

Develop a research attitude towards Data Science to continue developing scientifically.

Evaluate data:

Learn how to evaluate data-driven value creation within companies and organizations.

Communicate the results:

Experience analyzing Big Data from a variety of data sources and how to communicate the results.

Professors

BSE Professors are renowned researchers who are published in leading Economics Journals.

Associate Professor at Universitat Politècnica de Catalunya

Argimiro Arratia

UPF and BSE

Christian Brownlees

Assistant Professor, UPF

Lorenzo Cappello

Associate Professor, UPF

Robert Castelo

Blockchain Architect, FNZ Group

Craig Chatfield

Ramón y Cajal Fellow, UPF Artificial Intelligence and Machine Learning Group

Vicenç Gómez

Post-doc (UPF and BSE)

Jack Jewson

Assistant Professor, UAB

Toni Lozano

ICREA-UPF and BSE

Gábor Lugosi

UPF and BSE

Geert Mesters

MOVE, UAB and BSE

Pau Milán

Post-doctoral Researcher, UPF

Gergely Neu

UPF and BSE

Eulàlia Nualart

UPF and BSE

David Rossell

UPF and BSE

Alberto Santini

Research Associate, University College London

Hrvoje Stojic

Program Schedule

In September, students are required to take two brush-up courses: Introductory and intermediate computing for Data Science and A modern crash course in intermediate Statistics and Probability.

Students who can provide evidence of sufficient past course work may be exempt

Term 1 (September-December)

Course title	Credits	Professor(s)
Mandatory
Statistical Modeling and Inference	6	David Rossell , Geert Mesters
Deterministic Models and Optimization	6	Alberto Santini
Data Management	3	Sergi Nadal , Petar Jovanovic
Computational Machine Learning	3	Jack Jewson

Term 2 (January-March)

Course title	Credits	Professor(s)
Mandatory
Machine Learning	6	Gábor Lugosi
Computational Learning and Deep Learning	3	Toni Lozano
Machine Learning and Causal Inference	3	Robert Castelo , Federico Castelletti , Miquel Torrens
Electives
Probabilistic Inference in Machine Learning	3	Lorenzo Cappello
Networks: Concepts and Algorithms	3	Pau Milán
Geospatial Data Science and Economic Spatial Models	3
Macroeconomics and Finance: Financial Econometrics	6	Christian Brownlees
Introduction to Text Mining and Natural Language Processing	3	Hannes Mueller
Advanced Methods in Natural Language Processing	3	Arnault Gombert

Term 3 (April-June)

**Requires some prerequisite knowledges and authorization of the program director. Availability depending on suffcient demand

Course title	Credits	Professor(s)
Mandatory
Masater Project	6	Déborah Sulem
Electives
Industrial Practicum	6	Déborah Sulem
Reinforcement Learning	3	Gergely Neu
Machine Learning for Finance	3	Argimiro Arratia
Big Data management for Data Science	3	Besim Bilalli , Petar Jovanovic

Master’s Project

Students use the tools and knowledge they've acquired during the Master’s to explore a topic of their choice for the Master’s project. It can be carried out individually or in groups.

Examples of Master's Projects

Class of 2023

Leveraging Satellite Imagery to Assess Road Quality in the Democratic Republic of the Congo by Miguel Conner Bonmatí, Ramón Talvi Robledo, and Dominik Wielath.

Class of 2022

Risk Detection in Cryptocurrency Markets: Meeting the Needs of Traditional Finance by Iván Aguilar, Rebecca Jones, and Gian-Piero Lovicu.
Bayesian Optimization with uncertainty-aware neural networks by David Ampudia Vicente and Clinton Leung.
Sequential Monte Carlo for Approximate Variable Selection in Generalized Linear Models by Antoine Carnec and Maxim Fedotov.

Master’s degree awarded by UAB and UPF

Upon successful completion of the BSE Data Science Methodology Program, students will receive a Master’s Degree in Data Science awarded jointly with Universitat Autònoma de Barcelona (UAB) and Universitat Pompeu Fabra (UPF).

BSE Institutional Accreditations

Quality accreditations

All Barcelona School of Economics Master’s 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”).

Quality indicators for this Master’s degree

BSE commitment to quality

Placement rate

97%

Job titles: Data Analyst, Data Scientist.
Industries: Technology, Research and Academic Institutions, Financial Services, Consulting Firms.
Higher Education: 11% go on to a PhD or further education.
Companies: Accenture, Deloitte, European Central Bank, Glovo, Minsait.

Work Internationally

Cities with the most alumni

Barcelona

Amsterdam

Frankfurt

London

Testimonials

Data Science Methodology Program

Maria Salunina

A distinguishing feature of this intensive program is that it requires a great deal of independent research in teams, which resembles the natural business environment. This teaching approach allows students to develop into professionals who are able to find efficient solutions for different and unfamiliar problems…

Read less

Data Science Methodology Program

I Vivek Kai-wen

The programme’s strong focus on introducing the mathematical tools in areas like statistics and optimization was absolutely crucial to my understanding of Data Science methods and empowered me to choose the right set of tools each time…

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Why study a Master’s at BSE

1

Ranked among the top institutions for economics research in the world by RePEc.

2

Prestigious economists including Nobel Laureates guide the development of BSE Master’s.

3

Learn from well-renowned faculty.

4

Study in vibrant Barcelona.

Admissions and entry requirements

At BSE, we look for excellence. Key elements of a strong application are a high GPA, a sound statement of purpose, and standout reference letters. Strong knowledge of Economics and good quantitative skills are also recommended.

Master’s programs start: September 2025

Application deadline: July 2, 2025

Requirements:

An undergraduate/bachelor/grado/laurea, or equivalent degree from an accredited college or university (for Bologna degrees, a minimum of 180 ECTS are required).
University diploma in Economics, Finance, Engineering, Mathematics, Statistics, or Business Administration. Students with academic backgrounds in other subjects will be considered.
An advanced level of English language skills: TOEFL score of 90 or above; IELTS Academic Test score of 6.5 or above, Duolingo English Test 120 points.

Candidates will also be evaluated on the following admission criteria:

Outstanding academic record.
Quantitative skills.
Reference letters.

Apply now

FAQs

Below you will find our most frequently asked questions but do not hesitate to contact the BSE Admissions Team to learn more about our Master’s programs.