Master Econometrics Statistics

The Master's in Econometrics Statistics offers two distinct tracks in the second year, providing students with the opportunity to specialize either in research or in a professional pathway.
The first year of the program aims to establish a strong foundation in economics, econometrics, statistics, and Data Science. It familiarizes students with essential theoretical and practical tools to analyze contemporary economic issues and make informed decisions in the realms of business and administration.
The second year offers two orientations:

The research track develops advanced research skills, providing in-depth courses in economic, econometric, statistical methods, and Data Science. Students engage in research projects and write a thesis under the supervision of experienced researchers, preparing them for academic careers or research roles in the industry.
The professional track prepares students students for specialized positions in businesses or administrations. Upon completion of this track, our students will have acquired technical skills to manage and analyze large datasets, soft skills for communication, enabling them to pursue professional careers as Data Scientists or Data Analysts. This track emphasizes the practical application of data science techniques in concrete professional contexts. It also includes either an internship or an apprenticeship in a company, allowing students to apply their knowledge in a professional environment.

Graduates from the research track will have gained in-depth expertise in research and data analysis, while those from the professional track will possess practical skills to solve economic and statistical problems in a professional context. These two tracks thus offer diverse opportunities for students seeking a career focused on research or specialized professional positions.

The M1 is taught in French and in English, the student chooses the full English or the French/English curriculum.
The M2 is full English.

CAREER OPPORTUNITIES

Our students find jobs in France and abroad.
Examples of jobs held by our graduates: Data Scientist, Data Analyst, Statistician, Data Manager, Business Analyst, Quantitative Analyst, Consultant.

Watch the alumni talks on YouTube: https://www.youtube.com/c/AMSEChannel/playlists

Training flyer of the "Master Econometrics Statistics"

M1 Econometrics Statistics

M2 Econometrics Data Science (EDS)

This is a programme in Data Science built on solid statistical and econometric foundations. Students will learn how to code and apply machine learning techniques as well as interpret and communicate the results of their scientific projects. This will enable them to contribute to the industrial and administrative decision-making process by providing relevant and robust input.

Besides gaining a solid knowledge of state-of-the-art econometric and machine learning methods and their conditions of use, students will be trained to implement them on real data and to present the results, in oral or written form, to various audiences. Students will learn to use English in any professional context: converse in English, use technical vocabulary, understand documentation and scientific articles and write in English.

At the end of the M2, our students will have acquired the technical skills to manage and analyse massive data sets and the soft skills to communicate, which will enable them to pursue professional careers as Data Scientists or Data Analysts. The pedagogy is based on carrying out projects. The student’s capacity for analysis in a professional context, and therefore employability, is developed through an end-of-study internship, culminating in the writing and presentation of a report. Alternatively, students can select the apprenticeship track (“alternance/apprentissage”) in which they alternate between coursework at university and work in a firm.

Professional skills acquired by the end of the M2:

Ability to manipulate, analyse and interpret data using state-of-the-art machine learning techniques and econometric methods, irrespective of their nature (e.g. quantitative, qualitative, or unstructured data such as text and images) or size.
Competence in various programming languages (such as Python and R) and data science applications (such as dashboard visualisations), capacity to adapt quickly to any business environment.
Ability to independently choose the most appropriate machine learning tools and implement them in order to obtain reliable and robust answers that create added value for the company, or to provide public or private administrations with analyses useful in their operations.
Ability to communicate clearly, orally and in writing, the results of quantitative analyses to a variety of audiences such as non-specialist business managers or professional data scientists.

Alternatively, students can select into the apprenticeship track (“alternance/apprentissage”) in which they alternate between coursework at university and work in a firm.

In response to the internationalisation of professional opportunities, the Master's programme is taught entirely in English.

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Academic heads of the programme: Pierre MICHEL (pierre.michel[at]univ-amu.fr) and Badih GHATTAS (badih.ghattas[at]univ-amu.fr)
Administrative secretary: Emilie ALPACCA (emilie.alpacca[at]univ-amu.fr, tel : +33(0)4.13.94.44.22)

Training flyer of the "M2 EDS"

List of courses - Classic option

List of courses - Classic apprenticeship option

List of courses - Magistère option

List of courses - Magistère apprenticeship option