The standard version of the third year only concerns statistical engineering students. It seeks to provide them with a genuine specialization while at the same time introducing them to the professional world. Most of the teachers are from the professional sector, giving students an introduction to the sort of problems they will handle after graduation. This introduction is completed by professional seminars. From early April on, students go on a 5- to 6-month end-of-studies internship to apply what has been learned. Students work in the statistical, I.T., or economics departments of public or private companies, and learn how to draw on what they have learned and discover their future professional environment.
- Risk Management and Financial Engineering (Gestion des risques et Ingénierie financière)
This specialization meets the needs arising from rapid developments in financial markets and risk management practice as used by financial organizations. The multidisciplinary approach combines intensive use of statistics with stochastic modeling, numerical methods, and designing and improving C++ applications, thereby training engineers to be at the cutting edge of financial and technological innovation. The three broad areas of competence to which this specialization leads are: managing and regulating banking risk, investment allocation and strategies, innovation in financial engineering.
- Quantitative Marketing and Revenue Management (Marketing quantitatif et Revenue management)
A increasing importance is given today to studying consumer behavior in marketing decisions: market segmentation, development of new products and services, advertising strategies, choice of distribution channels, etc. This study is multidisciplinary in nature, blending mainly economics and statistics, but also psychology and sociology.
The Quantitative Marketing and Customer Relationship Management (CRM) specialization educates statistical engineers to be able to conduct such an analysis from pertinent models, allowing them to extract consumer tendencies and current or future market trends, and to make optimal decisions.
- Biostatistics (Statistique pour les sciences de la vie)
After complementary statistical training, especially in survival data, mixed models and sequential analysis, the courses provide students with the requisite tools for specializing in the experimental field. Courses in epidemiology, clinical trials, and experiment planning enable students to acquire a solid basis for health sector applications.
- Advanced Statistical Engineering (Génie statistique)
This specialization provides students with advanced skills in a range of applied statistics for industry, services, and the environment. Courses cover quality and reliability, image and signal processing, as well as forecasting and its applications, especially for the environmental sector.
- Data scientist specialization (Statistique et ingénierie des données)
This specialization allows students to refine and strengthen their knowledge of and skills in computer science and information processing tools so as to be on the same level as their statistical abilities. The training focuses on the culture surrounding computer science as well as in-depth presentations of the most recent technologies. In this way, the architecture, networks, project management, and the administration and management of database systems are covered along with data mining and warehousing learning techniques, object-oriented programming, web programming, and data security.
- Data Modeling for Spatial Analysis and Health Economics (Ingénierie statistique des territoires et de la santé)
This program aims to offer a background in statistical and econometric engineering at a very high-level applied to health economics and spatial dynamics. Students endeavor to master all of the tools necessary to implement the evaluation of public policies in the fields of health and territories. Statistical and econometric tools are the foundation of this program. The courses give a very detailed overview of territorial dynamics (labor market, migration, urbanization…) and health economics. Furthermore, the courses emphasize the economic evaluation of health and urban policies, increasingly important at national and international levels. Links between demography and health, urbanization and spatial economy, for example, are studied from public policy and statistical perspectives.
Particularly strong students who wish to carry out applied or theoretical research after ENSAI can benefit from the various facilities on offer during their studies: the possibility in their third year of following Master level 2 courses at universities with which ENSAI has concluded an agreement, thus enabling them to obtain a Masters’ and ENSAI engineering degree in tandem, privileged contact with university and Grande Ecole research laboratories and with the Center for Research in Economics and Statistics (CREST) that is part of the Grouping of National Economics and Statistics Schools (Groupe des Écoles Nationales d’Économie et Statistique). Students can also receive personalized supervision from a tutor specializing in the field of study in which they wish to conduct research, and may carry out their third-year internship in a research laboratory, etc.
Students are required to go on three internships during their studies in order to be awarded an ENSAI statistical engineering diploma. They are also required to spend a minimum of four weeks abroad, either as part of these internships, as a student in a foreign institution, or on a linguistic stay abroad.
At the end of their third year, students have to complete an end-of-studies internship of between twenty weeks and six months. It enables the students to apply what they have learned in their third year of specialized studies. This internship starts in April, and students write up a report on this period. They then have an oral defense in November. The jury, or panel, then decides whether or not to validate their internship on the basis of the report from the president of the jury.
Certain students can follow a course of study in a foreign university which counts as their third year. ENSAI has agreements with foreign institutions, and particularly through exchanges such as the UFA partnerships.
ENSAI students have also been known to independently complete their third year abroad at other institutions, and consequently return to ENSAI the following November for an oral examination of their year abroad. Neither of these possibilities is available to transfer students who arrive as second-year students.
Annual tuition fees (in 2018/2019) are €1,850 for statistical engineering students.
ENSAI awards scholarships to statistical engineering students on the basis of financial need.