• switch_etudiant
  • switch_entreprise


Admission for the 2014-2015 academic year is currently closed.


Dates and Deadlines

Information relative to the next admission cycle will be posted in Spring 2015.


E-mail: masterbigdata [at] ensai.fr
Phone: +33 (0)


MSc in Big Data


Master of Science in Big Data - Program Presentation brochure
(for all practical and pedagogical details) 

In 2016, there will be almost half a million jobs for qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.

- The McKinsey Global Institute, 2011

The demand for skills in the field of high-dimensional data processing, otherwise known as Big Data, is increasing dramatically worldwide, yet academic programs for this are still quite rare.

ENSAI is accredited by the French Ministry of Higher Education and Research to deliver a Master of Science in Big Data (known as a Master international or DNM in the French nomenclature).

ENSAI is currently the only French engineering school accredited to offer an all-English program with this unique training, combining Statistics and Computer Science.

ENSAI has many years of experience dispensing multidisciplinary training (Statistics, Computer Science, and Econometrics ), numerous international partnerships, a Big Data Academic Platform established by GENES, and a Big Data research chair financed by the Institut Louis Bachelier and the Fondation du Risque.

The Master of Science in Big Data offered by ENSAI therefore meets the very important need among corporations and organizations of all kinds for graduate-level training nearly non-existent in academic offerings on the French, European, and even international scale.

Program Presentation

Curriculum: Program Overview and Credits & Course Descriptions

The structure of this Master's program is composed of 2 semesters of coursework at ENSAI, followed by an internship within the professional world or academia/research laboratories.

Since this program welcomes students with varying academic levels and skills in Computer Science, Mathematics, and Statistics, the structure  aims to bring all students to the same scientific level in all three fields, with respect to their existing training, knowledge, and skills.

Therefore, in addition to common courses, the first semester includes courses tailored for students with different profiles. These courses take the form of two different tracks: Computer Science and Statistics, where students study the courses in which they need more training. 


Graduates of the program are skilled Data Scientists. In addition to doctoral possibilities in research, they will have numerous career opportunities in international corporations and data start-ups in the following areas:

- Digital Marketing
- Business Analytics
- Risk Management
- Yield Management
- Industrial applications
- Supply and distribution
- Healthcare industry
- Social networks analysis
- Research and development in scientific domains
- Software industry


All courses and examinations occur in English. Non-English speakers must have a minimum level of B2 (CEFR scale). Certificates requested with application form. 

Non-French speakers benefit from intensive French courses the preceding summer (July and August 2014), as well as weekly evening French classes during the academic year.

Foreign French-speaking students possessing an official French language certificate (DELF or DALF) may request to be exempt from some or all of the French courses.

Students possessing French nationality are exempt de facto.

Admission Requirements

This Master of Science in Big Data is open to students of all nationalities.

All applicants must have a minimum of 4 years of higher education (at least 4-year Bachelor's or the first year of a Master's). A strong mathematical and/or computer science background is required.

Applications are selected based on candidates' degrees, level, and skills. A personal interview (in person or via videoconference) will be at the discretion of ENSAI.

Application Procedure

The application period for this program is currently closed for the 2014-2015 academic year.

Information for the next admission cycle will be posted in Spring 2015.