Master in Data Science for Social Sciences

The master's program « Econometrics, Statistics - Data Science for Social Sciences » aims to give the students intending to pursue advanced professional careers or doctoral research a solid culture in economics and statistics, as well as in various related fields of applied mathematics.

• The first year of the international track « Data Science for Social Sciences » offers compulsory general courses in theoretical economics, econometrics, mathematical statistics and statistical software for data scientists, as well as optional specialization courses in mathematics and their applications such as, for instance, finance, data bases, optimization, Markov chains, martingales theory, probability modeling, and big data.
• The second year of this master emphasizes advanced and applied techniques in data science, statistics and econometrics. It offers deeper courses in data science, particularly in mathematics of machine and deep learning algorithms, data mining, big data, regulation of data spreading and data protection, as well as specialized courses in different fields of application of statistics to social sciences, such as spatial statistics and econometrics, graph theory and graph analytics, geomarketing, scoring, and web mining. Moreover, this second year of the program offers higher level courses of statistical software, namely R, Python and SAS, and of massive databases management. The different courses allow students to acquire versatile skills in the processing of complex data (panel, survey, survival, graph, spatial) with modern parametric, non-parametric, and learning statistical methods.

Apprenticeship

For prospective students interested in more on-the-job experience, the program can be adapted to allow following an apprenticeship (alternance) alongside the master's degree. From September to March, apprentices spend 3 days at the university (M-T-W) and 2 days in the company (Th-F). From April to August, they mainly work in the company. 

Program 2026-2027

M1 "Econometrics, Statistics" - Data Science for Social Sciences - International track

(Syllabi are updated regularly, non-contractual) Courses may change from one semester to another

* UE1/UE2/UE5 : A minimum grade of 10 out of 20 is required.

** Masters 2 Directors recommend attending certain options:

• Times series: M2 Statistics and Econometrics and M2 EEE
• Corporate Finance and Market Finance: M2 Finance
• Industrial Organization: M2 EMO

*** Math camp for M1 and M2 students

Bonus Points

Participation in sports or cultural activities, civic engagement or work-related activities may be eligible for bonus points. For further details, please refer to the French assessment guidelines (MCC) for the course shown opposite.

Program 2026-2027

M2 "Econometrics, Statistics" - Data Science for Social Sciences - International track

(Syllabi are updated regularly, non-contractual) Courses may change from one semester to another

* Courses in common with the 1st year Master.

** Students who have attended the Professional Development/Coaching course in 2025-2026 are exempted.

*** Maths refreshers courses for 1st and 2nd year master students

****Groups of 4 students

 (i) Students who have attended Project Management in M1 cannot register in M2.  And (i) Depending on the compatibility of the schedule

The capacity for each specialisation is set at 30 students for those studying the Econometrics and Statistics specialisation.

- Internship: duration typically of 6 months graded on the basis of the internship report and of the oral defense.

- Tutored projects: (a) the Statistical Consulting course (4 students per group) is a project proposed by a company and supervised by 2 teachers/researchers, with a report to be delivered to the client before the final defense; (b) collective projects (2 to 4 students per group) for several courses (e.g., Survey sampling, Non-parametric models, and Spatial Econometrics) supervised by a teacher, with a final oral defense.

- Master thesis (alternative option to the internship): topic of your choice, or suggested by a tutor, supervised by a teacher or a researcher, with a final oral defense in M2 and without defense in M1.

The second year of this master also exists as an apprenticeship track,  with some differences such as courses during holidays periods.  

Apprenticeship track

*: courses in common with the 1st year Master.

** Students who have attended the Professional Development/Coaching course in 2025-2026 are exempted.

*** Maths refreshers courses for 1st and 2nd year master students.

The capacity for each specialisation is set at 30 students for those studying the Econometrics and Statistics specialisation.

Bonus point

Participation in sports or cultural activities, civic engagement or work-related activities may be eligible for bonus points. For further details, please refer to the French assessment guidelines (MCC) for the course shown opposite.

At TSE, learning is enhanced by guest speakers, most of whom are professionals from various industries. These experts bring practical experience and real-world insights, complementing the teachings of our academic professors. This synergy provides students with a well-rounded education rooted in both theory and professional practice.

Semester 1, master 2

• Sylvia Gil Casals (Data Scientist, Microsoft, INSA Toulouse), Mathematics of Machine and Deep Learning Algorithms + Data mining
• Stéphane Malkawi (Business Analytics, Airbus), Statistical consulting
• Jean-Philippe Navarro (Expert in advanced modeling and probabilistic methods for end-to-end Airframe Design at Airbus), Statistical Consulting
• Louis Olive (Senior Quantitative Analyst, Banque de France), Scoring
• Valentin Guillet (IRT Engineer, Saint ExupéryAI & Robotics), Mathematics of Machine and Deep Learning Algorithms

Semester 2, master 2

• Raphaël Danjou (CGI associate | Expert Conseil Data Gouvernance), Datanomics
• Nicolas Le Gall (Data Scientist at Aqsone), Big data
• Van Duy NGO (PhD candidate, IRIT),  Data bases
• Marion Hoffman (Mathematical Sociologist, IAST), Graph analysis
• Marijn Keuzer (Sociologist and Research Fellow at IAST) Graph analysis
• Lynda Lechani (professor at Paul Sabatier), Web mining
• Stéphane Malkawi (Data Science, Business Analytics at Airbus), Statistical consulting
• Jean-Philippe Navarro (Expert in advanced modeling and probabilistic methods for end-to-end Airframe Design at Airbus), Statistical Consulting
• Claire Vaufrey (teacher at ENAC), Project Management

This international track aims to train "data scientists", "data analysts", "project managers", "engineers” and/or “consultants" in statistics with backgrounds in economics and econometrics. The graduates benefit from direct professional integration not only in the tertiary sector (e.g. quantitative marketing, banking, insurance), but also in industry and academic research.

Admission is based on academic excellence. 

Courses are entirely taught in English: a C1 English language certificate may be required depending on the applicant’s profile (IELTS Academic, TOEFL iBT or CAE).

Applicants who do not hold a degree obtained in the French higher education system are required to submit GRE test results.

Applications are submitted through TSE's eCandidatures platform.

First year admission:

TSE students will be admitted provided they validated their undergraduate degree in Economics and Mathematics. Students from other undergraduate programs may apply if they have excellent results in key subjects of the D3S program.

External students may apply if they successfully completed a BA or BSc in Economics, Mathematics or Data Science.

Second year admission:

TSE students who passed their M1 D3S will be automatically admitted. Students from other M1 programs may apply if they have excellent results in key subjects of the D3S program. 

External students may apply if they successfully completed a 4-year undergraduate degree or a Master’s degree in the fields of Economics, Mathematics or Data science. 

Apply to the D3S program