Data Science for Decision Making

Overview

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 Barcelona School of Economics 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 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.

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.

Here is a brief profile of the classmates that a Master's student in the BSE Class of 2022 will meet this year:

• Most students have undergraduate degrees in Economics or Finance. Others come from Engineering, Mathematics, or other backgrounds. 
• Most of the students has work experience before joining BSE, but there are other students who were accepted to pursue the Master's programs immediately after obtaining their undergraduate degrees.
• All continents are represented in the Class of 2022. This year, students come from 49 different countries, with 86% of students coming from outside of Spain and 44% of students coming from outside Europe.

Accreditation

All Barcelona School of Economics Master's degrees have been recognized by the Catalan and Spanish Education authorities and within the framework of the Bologna Process (in Spanish, “Master Universitario o Master Oficial”).

The Barcelona School of Economics has been distinguished as a Severo Ochoa Center of Excellence in every edition of the program (2012-15; 2016-19; 2020-23)