Data Science, statistics and learning


The “Data Science” major enables to acquire a highly qualified profile in statistics and applied econometrics for which opportunities in the labor market are extremely varied, from data scientist through lecturer, to consulting and public or industrial statistic expertise. Depending on the options selected, these practical skills will go along theoretical expertise in social sciences (economics, sociology), marketing, applied mathematics (probability, statistics) and possibly basic biology skills.

Such trained “Data Scientist” have a scientific expertise of the highest level that allows them to support decision-making in many areas: public policy assessment, firm trade policies assessment, finance, biostatistics, imaging, survey statistics, or performing basic research. This versatile profile can lead to both expert careers and decision-making positions in business or coaching.


For several years, there has been an explosion in the volume of data available in a variety of areas (e.g. genetics, neuroscience, climatology, as well as finance, marketing and human and social sciences). After a period when questions focused on the storage and preservation of these data, problems related to statistical evaluation and analysis now appear as involving important issues. The created jobs require both technical skills and a strategic understanding of the underlying issues.

The cross-disciplinary nature of the quantitative methods presented in this major allows students to access to a wide range of jobs in both public and private sectors. This major develops, among other things, the skills expected for the “chief data officer” positions that are emerging in the context related to “Big Data”.

The Statistics and Learning unit aims to develop statistical models, to find or build databases (experimental design, pre-treatment, etc.) and organize tests or statistical learning to support decision-making under bounded rationality. It offers courses in different areas: those related to statistical surveys lead to methodologists positions in polling institutes, statistical and studies services of large companies and administrations, and among consulting firms; courses oriented towards learning and high-dimensional statistics lead to statistical expert professions in the industry and large companies using large databases such as Google or Amazon, but also in technology startups. These teachings are supported by basic theory courses and also lead to research in statistics.