Overview

The Master in Data Science and Banking program aims to provide students with the knowledge and skills necessary to employ data science and artificial intelligence techniques to address challenges facing the banking sector, such as fraud detection, risk modeling, customer behavior analysis, and future value prediction. This program combines theoretical and applied aspects, focusing on the use of machine learning and predictive analytics tools to improve decision-making and enhance organizational performance. This specialization responds to the growing need among financial institutions for personnel capable of understanding and analyzing big data and transforming it into effective strategic decisions.

Goals

Strengthen students’ knowledge of current issues and evolving technologies in data science and bank management.
Promote in students an understanding of the importance of data analytics to the banking industry.
Provide the student with the analytical expertise to research and evaluate customer and financial data.
Equip students with the ability to apply data science tools and techniques to further a banking organization’s risk management and strategic goals.
Develop the student’s ability to use data mining and data analytics to formulate profitable financial strategies for a bank.
Enable the student to assume a leadership role in the banking industry.

Career of Graduates

Graduates of this program are expected to be qualified to work in different fields such as:

Banking Data Analyst.
Data Scientist in the Banking Sector.
Business Intelligence Expert.
Machine Learning Engineer in the Financial Sector.
Financial Data Engineer.
Data Analytics Manager in Banks and Financial Institutions.
Data-Driven Marketing Analyst.
Academic Researcher or Lecturer in the Field of Financial Data.

Program Learning Outcomes

Upon completion of this program, students should be equipped with comprehensive knowledge, skills, and abilities to excel in their endeavors.

Banking Fundamentals

Demonstrate proficiency in the fundamental business principles and practices of banking.

Emerging Trends in Data & Banking

Examine and evaluate new developments in data science and bank management.

Data Mining for Financial Decisions

Use data mining to analyze and interpret data to make optimal financial decisions for a banking organization.

Customer Analysis & Product Innovation

Analyze bank customers and propose innovative and profitable financial products for bank customers.

Credit Analysis & Risk Management

Employ critical thinking to research and analyze credit data and evaluate loan risk, customize offerings and mitigate fraud.

Risk-Return Optimization with Data Science

Evaluate the trade-off between risk and return and employ data science tools and techniques to seek opportunities for increased returns on investments.

Leadership & Innovation in Banking

Develop leadership and management practices that promote innovation and change in banking.

Success Stories

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University Scholarship for Master's Degree

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