Master's Degree in Data Science: Data Science for Decision Making Program

Program Director


Hannes Mueller

PhD, London School of Economics


Steering Committee


Christian Fons-Rosen

PhD, London School of Economics

University of California, Merced


Pau Milán

PhD, Universitat Pompeu Fabra


The demand for Data Scientists is exploding, driven by the increasing availability of data and the advance of machine learning. Data collection and analysis have become crucial components of decision making in today’s private and public organizations and many have started to develop specialized departments for this purpose.

The ability to extract, handle, and analyze large amounts of data is therefore a key skill on today’s job market.

However, gathering and summarizing data is not enough. Data science can only improve decision making with an understanding of how choices affect outcomes. Data Scientists must therefore increasingly combine standard tools in machine learning with an understanding of the causal relationships behind the data.

The BSE Master's Program in Data Science for Decision Making integrates key elements from Data Science and Economics to give graduates the ability to deal with all types of data and make the correct inferences from it.

Students will be trained in the use of cutting-edge machine learning methods and of statistical models that will help them to provide effective data support in the decision-making process of any organization. Students will, for example, be able to extract information from the structure of social networks, satellite images, large libraries of digitized text, read and visualize data in maps and make sense of geo-localized information and time series data. They will also be able to use this data for forecasting and evaluate different policy options or business strategies through models built on an understanding of causal relationships.

Study with leading researchers and practitioners

Data Science for Decision Makers integrates different approaches from Data Science, Statistics, Econometrics and Economics in a unique program taught by leading academics in the fields of Economics, Operations, and Statistics, as well as experienced professionals from the analytics industry and public policy consultants from organizations.

Work with real data on interdisciplinary teams

Students learn with real data to solve decision-making problems hands-on through homework, applied training sessions, and an independent Master's project.

The collaborative environment of the program will expose students to working with colleagues from many different academic and professional backgrounds on interdisciplinary teams.

The Data Science for Decision Making Master's offers a special way to bring skills we teach in the program to real-life problems: the Barcelona School of Economics Master's Thesis Challenge! The challenge allows outside organizations to submit problems that are then tackled by small student groups. The solution is then submitted as a Master's thesis and presented in front of the respective organization.

Here are some of the organizations BSE student teams are working with:

  • Columbian Energy, Predictive Modeling for Day-Ahead Pricing in Electricity Markets: A Methodological Approach for Colombia
  • Glovo, Analyzing the Impact of Stock-Outs on Sales of Products in an Online Delivery Application
  • Innova, BiciMAD: Bike-Sharing System Dataset Creation and Preliminary Hourly Demand Prediction using Machine and Deep Learning Approaches
  • Koa Health, Behavioural predictors of personality inferred by passive smartphone sensing
  • Novartis, Decoding Abnormal Returns: Unraveling Insights from Pharmaceutical Sector Earnings Calls through Graph-Enhanced Text Analysis
  • Novartis, Comparative Analysis of Modeling Approaches for Value-at-Risk Forecasting in the Pharmaceutical Sector: An econometric and ML approach
  • Oxera, Automated Feature Extraction from EU Merger Documents: Novel Approaches using LLMs
  • UNDP / UNICEF, Harnessing Big Data News Media For Conflict Prediction and Anticipatory Decision-Making
  • UNHCR, Forecasting Global Refugee Flows: A Machine Learning approach using non-conventional data
  • Virtuleap, Harnessing Big Data News Media For Conflict Prediction and Anticipatory Decision-Making

Is “Data Science for Decision Making” for you?

The Decision Making track is tailored to accommodate both recent graduates and those with work experience in private and public organizations. All students will benefit from a combination of training in programming, theoretical model techniques and hands-on applications which will allow them advance any decision making process in any organization. Students with work experience will be able to see the data in their own work environment with completely new eyes and realize the potential of untapped data resources like text and images.

Program schedule: 

The Data Science for Decision Making Program is organized around four pillars:

  • Statistics and Machine Learning
  • Econometrics and Causal Identification
  • Data Warehousing, Business Intelligence, and Text Mining
  • Economics Models and Optimization for Decision-Making

Watch the following video for a quick overview of the course in Forecasting and Nowcasting with Text as Data, then browse the full course list below:

Forecasting and Nowcasting with Text as Data
Prof. Hannes Mueller (IAE-CSIC and BSE), Program Director

The course offer displayed is for next year's edition. Course offer is subject to change.

Course list for current students


Master project

The master project is a required component of all BSE Master's programs. Working individually or in groups, students use the tools and knowledge they've acquired during the entire year to explore a topic of their choice. A professor supervises throughout the project.

Examples of master projects from previous cohorts:

Master's degree awarded

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

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”).

What skills and knowledge will I acquire in this program?
  • Ability to provide adequate data analysis for decision-making problems in research, governments, firms, international organizations and NGOs.
  • Ability to analyze the decision-making problem through the combination of applied data science and economics frameworks.
  • Programming skills necessary to extract data from any source including text, images, social networks, geocodes and maps.
    • Use and program cutting edge machine learning and econometric tools to analyze the resulting data.
    • Gain expertise in database management and distributed processing in a cloud computing environment.
    • Develop a deep understanding of the differences between correlation and causality and why this is crucial for optimal decision-making.
    • Communicate data analysis results effectively through presentation and aesthetic charting skills.
  • Ability to approach problems from different angles and to be aware of complementarities in knowledge on interdisciplinary teams.
Who will benefit from this program?

The goal of this Master's program is to serve two profiles:

  • The applied nature of the course aims to be accessible to students that have work experience in enterprises, government or international organizations and have worked with data inside these organizations.
  • The program gives recent graduates with strong analytical skills the possibility to specialize in applied data work.

Given the diverse background of our students, there are no prerequisites in either Data Science or Economics. However, students will only be able to absorb the wealth of methods that are taught with some experience of working with data, very strong quantitative skills, and some prior knowledge in Statistics.

Students will learn how to use STATA and program in Python during the Master's, but some experience in these two software packages will allow students to focus on the applications.

Who hires Data Science for Decision Making graduates?
  • Research and Academic Institutions
  • Tech Firms
  • Government and Authorities
  • International Organizations and Non-profits
  • Consulting Firms

Examples of recent placements:

  • Central Bank of Malta  - Economist Researcher (Valletta, Malta)
  • Fundació d'Economia Analítica (FEA) - Data Scientist (London, United Kingdom)
  • Glovo - Product Data Analyst (Barcelona, Spain)
  • HP - Analytics Intern (Barcelona, Spain)
  • IAE-CSIC - Research Assistant (Barcelona, Spain)
  • Ministry of Finance of Chile - Budget Department - Analyst (Santiago, Chile)
  • OECD - Consultant (Big Data and Labour Markets Analyst) (Paris, France)
  • PepsiCo - Data Scientist (Barcelona, Spain)
  • Ricoh - Data Scientist (Marketing and Sales) (Barcelona, Spain)
  • RTLab - Geo-spatial Data Scientist (Barcelona, Spain)
  • World Bank - Consultant (Washington, DC, United States)

Alumni career paths in more detail

Can I enter another BSE Master's directly from this program?

Students who successfully complete the Data Science for Decision Making Program are eligible for direct admission to the following programs, if they stay for a second consecutive year:

Master’s Degree in Economics and Finance:


Master’s Degree in Specialized Economic Analysis:

A 20% discount will be applied on the second program's tuition fees. All BSE Alumni are eligible for this discount at any time.

Read more about taking a second BSE Master’s degree



Data Science for Decision Making Student Profile 2023-24

25 students from 17 countries (80% international)

Most represented countries this year:

  • Spain (5)
  • France, Germany, United Kingdom, United States (2 students each)

Most common academic backgrounds:

  • Economics
  • Computer Science
Chart displays years of work experience at BSE in Data Science Students


Data Science for Decision Making alumni career paths

Overview of Data Science for Decision Making career paths from the first two cohorts (2022 & 2023)

  • Most common job titles:
    Data Analyst, Data Scientist, Consultant
  • Most common industries:
    Technology, Banking, Government and Authorities
  • Cities with the most Data Science for Decision Making alumni:
    Barcelona, Paris, Copenhagen, Washington DC, New York
Data Science for Decision Making Program Placement by Industry