M2MO: Modélisation Aléatoire, Finance et Data Science

Master en statistique, probabilités et finance - Université Paris 7 - Paris Diderot

 
 
 
 
 
 
Presentation of M2MO for international students
 
 

Presentation of M2MO for international students

M2MO is a top-level one-year master program in probability and statistics with specialization in quantitative finance or in data science.

The finance track offers courses in all aspects of modern quantitative finance starting from the basics of option pricing to more advanced subjects like volatility surface modeling, advanced interest rate models, credit risk, portfolio management etc.

The data science track offers courses in statistical learning, advanced techniques for big data, treatment of massive data sets and on applications of these methodologies in an industrial environment.

Our alumni are hired by quantitative research and risk management teams of major international banks (mostly in Paris and London), insurance companies, and by statistical departments of other major industrial actors. Alternatively, after a PhD thesis in a relevant field, M2MO offers access to research and faculty positions in the academia.

The program starts around mid-September and is structured in three two-month periods (trimesters) of intensive courses, followed by a 5-6 month industrial internship from mid-April to the end of September. During the first 2 months of the program, students of both tracks follow intensive courses on the theory of stochastic process and advanced statistical methods. The second and the third trimesters are dedicated to elective courses in the chosen specialization domains.

The M2MO is formally a second-year master program, which means that admission is open to students who possess a French M1-level degree or equivalent. International students typically come when they already have a master's degree in mathematics and want to acquire a top-notch specialization in quantitative finance or data science.

The tuition fee is 3700 euros for the whole administrative year.