Random modeling and scientific computing study track

pictogramme cœurFor those who like

 

  • Probability
  • Data analysis
  • Mathematics and applications (in finance, data science, etc.)

Objectives

The track provides training in applied mathematics, specifically in the fields of random modeling and scientific computing for applications (according to choice) in financial mathematics, data science, modeling and signal and image processing.

In practice

We take an in-depth look at mathematical tools for statistics, scientific computing and financial mathematics. The theoretical approach is similar to that of a preparatory class, with seminars and practical sessions completed in R. The Masters 2 completed thereafter often focuses on probability, finance or statistics.

Language of instruction: English

After the track

3rd year technological innovation at Télécom Paris

Master’s-Engineering Dual Degree

  • Random modeling, finance and data science (Univ. Paris-Cité)
  • Probability & Finance (IP Paris)
  • Data Science (IP Paris)
  • Statistics, Finance and actuarial science (IP Paris)
  • Mathematics of randomness (IP Paris)
  • Mathematics, Vision, Learning (IP Paris/Univ. Paris-Saclay)

Professions

Technology companies and the financial industry particularly appreciate dual degrees from this Master’s program. This type of program opens vast opportunities for PhD students to pursue an academic thesis or an industrial project (CIFRE thesis).

Testimonials

I loved this study track! It’s a demanding but incredibly rewarding course. You develop real mathematical rigour and learn all the basics you need to understand market finance: probability, statistics, stochastic calculus, etc.
Thanks to this course, I was able to get into the Master of Finance at MIT, and I quickly realised how much everything I had learnt here helped me to approach quantitative finance in a solid and structured way.
I would really recommend this course to anyone interested in applied mathematics, data or finance.
Victoire Marcaillou, class of 2025 (Master of Finance at MIT)

Anna Van Elst

It is an excellent track for those who love probability and theoretical mathematics. It covers all the key probability concepts: mathematical statistics, stochastic calculus, modes of convergence, and martingales.
I especially appreciated the quality of the demonstrations and the diversity of the mathematical reasoning. In addition, this track helped me understand the tools used in data science and mathematical finance.
The track also paves the way for excellent opportunities in the best applied mathematics Master’s programs (Probability & Finance, Mathematics, Vision, Learning…).
Anna Van Elst, class of 2023

Managers

Head: François Roueff
Head of international mobility: Anne Sabourin
Internship coordination: Laurent Decreusefond