Master in Finance and Big Data (MSc) - NEOMA (Paris)

The Master of Science Finance & Big Data consists of seven modules that combine know-how and interpersonal skills. The skills taught in this programme enable learners to become experts in specialised financial engineering applied to big data processing where the graduates will master theoretical and operational aspects of data science applied to finance.

In addition to this imparted knowledge, many different professional skills are put into practice so that the students can be immediately effective at their companies.

This programme enables students to:

1. Master the programming languages used in data processing.
2. Analyse and manage financial data.
3. Master the valuation concepts for financial products.
4. Apply the acquired data science techniques in real situations.
5. Independently manage a project requiring big data extraction and processing skills.

The MSc Finance & Big Data is intended for students and professionally active managers who want to undertake additional training and specialise in all the professions associated with data science applied to the financial sector. Its part-time schedule is compatible with professional activity.

All of this programme’s courses are taught completely in English.

The MSc Finance & Big Data programme is based on four skill fields:

1. Identify and promote companies, sectors and/or markets with high potential for added-value creation in France and abroad

2. Make or support decisions concerning financial investments in France and/or abroad while overseeing associated risk control

3. Guide financial decisions and associated risks using financial-decision analysis and monitoring tools

4. Create and implement data-based descriptive and forecast models to facilitate the financial analysis of companies, sectors and/or markets


This programme is accessible via the « VAE » (awarding a qualification based on relevant professional experience).

DATA USE

Exploration of big data through simulations and practical studies that companies present during the courses.


BIG DATA APPLICATION IN FINANCE

Digital methods and AI in the following areas:

1. Portfolio allocation
2. Financial market forecast models
3. Detecting market sentiment
4. Algorithmic trading
5. High-Frequency Trading

The professional thesis is a project whose purpose is to identify an issue important to companies and respond to it by using a conceptual approach and empirical research.

This project must lead to practical recommendations for companies. Its additional purpose is to help students acquire technical expertise while also developing important soft skills for the job market: critical thinking, complex problem resolution, etc.

The programme is recognised through a dual validation:

1. Ongoing assessment: evaluations conducted throughout the length of the programme in the form of individual or collective reports to be submitted

2. A professional thesis: submission of a written document and an oral defence before a jury made up of 2 tutors and the programme directors


At the end of the programme and after a validation of the ongoing assessment and professional thesis, the Level-7 RNCP of International Financial Analyst, Strategy and Financial Management degree is awarded to the participants.

If some modules were not validated and thus no credits were earned, the programme participant can redo the evaluation during a period set up for this purpose.