MBA Finance & Data Performance
INTRODUCTION
Program description
The Eslsca Paris Business School's MBA2 Finance and Data Performance is a high-level program of excellence that targets profiles with strong quantitative dominance. It is part of digital finance and big data analysis and meets the new requirements of the finance professions (banking, insurance, financial and investment institutions, financial markets, etc.).
The MBA 2 Finance and Data Performance combines solid knowledge in quantitative finance and risk management with skills in data analysis. The objective of the program is to master digital transformation processes both at the level of market infrastructure and the value chains of financial activities. The MBA 2-Finance and Data Performance is distinguished by its selectivity and its quantitative borrowing. The originality of Eslsca’s new program in Finance and Data Performance lies in its ability to create bridges between traditional professions in finance and new professions in data analysis. The program is aimed at financiers who want to move into Data-oriented professions as well as various Data profiles wishing to specialize in finance. The MBA 2-Finance and Data Performance program is built in the interference of three spheres: Finance, Mathematics and Data Science.
Objectives
- Master the tools for extracting, analyzing, mining and restoring data.
- Master the methods and techniques of processing big data (Big Data) and machine learning techniques (Machine Learning & Deep Learning).
- Acquire the necessary skills in finance and Data Analysis allowing them to adapt to the disruptions in finance in the digital age.
- Control all innovations, services, products or organizations related to digital technology, likely to modify the finance professions.
- Understand the new rules of the game on the financial markets and the role of the different players (traditional players, new players, regulators, etc.)
Courses Program
- Actuarial calculation and financial products
- Quantitative portfolio management techniques
- Valuation of assets and derivatives
- Advanced econometrics applied to finance
- Financial risk management
- Bank risk management
- Quantitative risk management
- Extreme risk statistics
- Multiple risk management
- Digital financial market infrastructure
- Blockchain in Finance
- Fintech in Corporate Finance
- Fintech in Capital Markets
- Means of payment and financial regulation
- Cloud Computing (AWS)
- VBA
- SQL databases
- NoSQL databases
- Data Analysis
- Data Visualization (Power BI)
- Big Data & Machine Learning in Finance
- Phyton & data science in quantitative finance
- Quantitative finance under R
- Deep Learning in Finance
- Cryptography and data security
- Pilot the digital transformation of finance professions
- Lead a Big Data project in the field of finance
Skills
- Master the quantitative approaches of financial engineering
- Master and develop quantitative techniques for managing risks and emerging risks
- Pilot financial innovation processes and support the digitization of means of payment and financial market infrastructure
- Master the fundamentals of data analysis and Big data
- Enrich and support decision support systems through multidimensional modeling
- Pilot the digital transformation of finance professions
- Lead a Big Data project in the field of finance
Teaching method
The ESLSCA method is based on three pillars:
- Theoretical academic knowledge
- Experiential through the application of lessons in the form of business cases, business games but also Open Innovation challenges and concrete projects / missions promoting the spirit of innovation and entrepreneurship and collective intelligence
- Validation via internships and work-study programs, sharing in the form of conferences, masterclasses and exchanges with alumni, etc.
In addition, the Eslsca learning method enhances the profile of the "Augmented Manager 4.0"; this must reconcile hard skills, soft skills, digital skills and business skills in order to adapt to the reality of the labor market and ensure maximum employability.
MBA 2nd year
- BAC + 4 (validated or in the process of being validated) specializing in Finance, mathematics, applied economics, statistics, econometrics, etc.
- BAC + 4 (validated or in the process of being validated) with a quantitative profile and solid foundations in mathematics, econometrics and statistics
- Engineer title for all specialties
- Open to senior business executives with experience in quantitative finance.
- CV + Questionnaire followed by a motivational interview
Career perspectives
Trained students can apply for the following professions following this MBA:
- Finance jobs: Asset Manager, Risk Manager, Trader, Quantitative Analyst, Actuarial, Credit Analyst, etc.
- Data professions: Data Analyst, Data Manger, Data Miner, Business Intelligence Manager etc.
They are eligible for the following sectors of activity:
- Financial markets,
- Bank and insurance,
- Audit firms,
- Research and consulting companies
- Industrial and commercial enterprises
- Accounting firms