MBA Finance & Data Performance
- From €13,100/year 2025-2026
- October 2025
- French
Program description
The MBA in Finance and Data Performance at ESLSCA Paris Business School is a programme of excellence aimed at profiles with a strong quantitative bias. Focusing on quantitative finance and the analysis of massive data, it meets the current needs of the financial sector (banking, insurance, financial institutions, financial markets, etc.) as well as those of Data Science.
This MBA combines solid knowledge of quantitative finance and risk management with skills in data science. It also enables students to master the digital transformation of both financial markets and finance-related activities.
The MBA in Finance and Data Performance stands out for its selectivity and quantitative approach. Its originality lies in its ability to build bridges between the traditional professions of finance and the new professions of Data Science. It is aimed both at financial professionals wishing to specialise in Data Science and at Data profiles wishing to move into the financial sector.
The programme is based on three fundamental pillars: Mathematics, Finance and Data Science. Thanks to this MBA, students acquire the skills they need to succeed in a constantly changing environment, where the quantity and quality of data are essential for making strategic and competitive decisions.
MBA objectives
- Mastering data extraction (APIs), analysis, mining and retrieval tools
- Master the methods and techniques for processing massive data (Big Data) and machine learning techniques (Machine Learning & Deep Learning)
- Acquire the necessary skills in Finance and Data Science to adapt to the disruptions in finance in the age of digitalisation
- Understand all the innovations, services, products and organisations linked to digital technology that are likely to change the way finance works
- Understand the new rules of the game on financial markets and the role of the various players (traditional players, new players, regulators, etc.)
MBA Finance & Data performance 2025/2026 programme
Teaching methods:
Face-to-face: 90% | Online: 10%
Lectures: 60% | Tutorials: 40%
Module 1 - Finance and quantitative engineering
- Banking - Financial intermediation - Financial markets
- Advanced accounting
- Portfolio management
- Financial management
Module 2 - Quantitative risk management
- Risk management
- Derivatives
- Mission Finance data +
Module 3 - The fundamentals of Big Data
- Algorithms
- Big Data
- Statistical and Probability Tools
- Python
- Econometrics
Module 4 - Big data and machine learning in finance
- NoSQL
- Machine Learning
- Mathematics & Data Science / Python
- VBA and Python Programming for Finance
Module 5 - Compliance
- SD/CSR
- International accounting standards (IFRS)
- Corporate taxation
Module 6: Developing professional skills
- TOEIC preparation
- Financial English
- Lectures and visits
- Skills passport
- CV and interviews
2-month work placement (i.e. 44 days in a company) for initial training students
Module 1: Finance and quantitative engineering
- Financial modelling and languages
- Valuation of assets and derivatives
- Quantitative portfolio management techniques
- In-depth econometrics
- Parallel computing
Module 2: Quantitative Risk Management
- Financial Risk Management
- Quantitative Risk Management
- Banking Risk Management
Module 3: Digital Finance
- Project management/AMOA/PMO
- Robotic process automation (RPA)
- Blockchain and cryptocurrency
- Fintech and innovation
Module 4: Big Data Fundamentals
- SQL database
- Statistical tools and probabilities
- Big Data ecosystem
- Unstructured databases
Module 5: Big Data and machine learning in finance
- Data analysis in finance
- Data science project for finance
- Machine learning and deep learning in finance
Module 6: Compliance
- Financial market law and regulation
- Data governance
- Data regulation
Module 7: Producing macroeconomic and geopolitical analyses with an impact on financial markets
- Economic and financial intelligence
- Company valuation
- Data visualisation (Power BI)
Module 8: Developing professional skills
- TOEIC preparation
- Financial english
- Soft skills
- Visits/conferences
- Skills passport
4-month work placement (i.e. 88 days in a company) for initial training students
Target skills
- Use massive data and quantitative techniques to model risks and anticipate financial market trends
- Analyse the valuations of different types of assets or benchmark indices to guide intervention decisions on the financial markets
- Design and structure complex financial products to optimise the return on a portfolio of assets
- Activate mathematical models and AI through software tools to optimise financial transactions on the buy and sell side
- Check the compliance of financial market intervention procedures to ensure the quality and security of transactions
Registration is open all year round and closes once the number of students has been reached (places are limited per class).
Registration deadline: October 2, 2025. After these dates, please contact the admissions department at [email protected]
Admissions procedure
- CV
- Questionnaire
- Motivational interview
Prerequisites
- For entry to MBA 1
Hold (or be in the process of obtaining) a bachelor's degree (bac +3) in mathematics, statistics, econometrics, finance, economics or management.
- For entry to MBA 2
Hold (or be in the process of obtaining) a 4-year degree in mathematics and applications (economics, finance, sociology, decision support systems, etc.), statistics and probability, econometrics, applied economics, economic modelling or quantitative finance.
Diploma Recognition
Establishment diploma preparing for the professional qualification of "Expert in financial markets and instruments", a professional qualification registered with the RNCP on 19/07/2024 under number 39400 for a period of 5 years, code NSF 313, awarded by the "Ecole supérieure libre des sciences commerciales appliquées", a qualification accessible via the VAE system.
Career perspectives
The students trained can apply for the following professions following this MBA:
Finance professions :
- Asset Manager
- Risk Manager
- Trader
- Quantitative Analyst
- Actuary
- Credit Analyst
Data professions :
- Data Scientist
- Data Analyst
- Data Manager
- Data Enginer
- Business Intelligence Manager
Evaluation methods
The study year is divided into two semesters, with the last week reserved for exams.
Grading conforms to the ECTS (European Credit Transfer and Accumulation System) standard promoted by the European Union. The assessment system complies with the 2025-2026 internal study regulations; the average grade for a course or module is used to assess the efforts made by each student, and to help them make the right academic and professional choices.
It includes elements of continuous assessment, the evaluation of various assignments and the grade obtained in semester tests.
Under the direction of the School Director, the school jury meets once a year to decide on the case of each student (passing, repeating, reorientation).
A student validates his or her year with 60 ECTS (i.e. 30 ECTS per semester) and an average of 10/20 per module, bearing in mind that 5 is an eliminatory mark for a course..
In addition, all pedagogical requirements must be met:
- Compulsory 4-month MBA 2 internship with internship report
- MBA 2D final year dissertation
- Personal development (participation in school life)
Any student who fails to obtain an average of 10/20 in a module will be invited to the make-up session to retake the exams defined by the passing jury.
If a block is not validated after the make-up session, the student must repeat the year and does not retain the benefit of potentially validated blocks.
A second School Jury will be held after the catch-up session to decide on the case of each student: conditional passage for 2-year alternating students, repetition, reorientation, exclusion, gap year.
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