Financial Services Analytics (FSA) is the science and technology of creating data-driven decision-making analytics for the financial services industry. Data-driven insights and analytics increase the effectiveness of business operations, enhance customer relationships, improve product offerings and improve risk analysis and risk management. The Harvard Business Review refers to data science and analytics as the “sexiest job in the twenty-first century."

Intended to meet the growing global need for professionals with expertise in data analytics, the FSA certificate will empower students with an array of statistical learning methods and database skills in order to create end-to-end business decision making data analytic tools from an enterprise level systems approach.
Students who complete the certificate will gain a substantial competitive edge in pursuing a career as:

  • Data Scientist
  • Systems Analyst
  • Business Analyst
  • Quantitative Analyst
  • Visualization Designer
  • Software Engineer 

Curriculum – 15 credits

FE 582 Foundations of Financial Data Science - 2 credits
FE 513 Practical Aspects of Database Design (lab) - 1 credit
FE 590 Introduction to Knowledge Engineering - 3 credits
FE 595 Financial Systems Technology (Analytical Financial Systems Design) - 3 credits
FE 550 Data Visualization Applications - 3 credits
FE 800 Special Projects in Financial Engineering - 3 credits

Students can apply the 15 credits from the FSA certificate towards a master's degree in financial engineering, engineering management or systems engineering.

Current Stevens students can apply for the FSA program by completing the Add/Change form. All Stevens students who apply for the FSA program will be considered for the Accenture scholarship.

Program Benefits

  • Understand different data types such as big data or text data and be able to address specific data extraction, storage and retrieval issues. Learn optimum methods of data representation along with various data scrubbing techniques
  • Manage various database techniques such as SQL, Hadoop, and NoSQL
  • Learn statistical learning methods and information extraction
  • Understand the basics of text analytics and network analysis
  • Code various analytical techniques using R or Python
  • Create end-to-end business decision-making data analytics along with enterprise level systems thinking
  • Optimize financial data visualization techniques

Admission Requirements

  • Completed application for admission
  • Students who apply for admission to the certificate program must have an undergraduate degree in an engineering, science, finance or related field and prior coursework in calculus, probability and statistics. Knowledge of a programming language is preferred. Preparatory courses are available
  • Students who plan to pursue a master’s in FE must apply separately and must meet additional prerequisites in differential equations, linear algebra and a programming language
  • Official college transcripts from all colleges attended
  • Two letters of recommendation
  • GRE/GMAT scores (Not required for part-time students)

For more information on the FSA program, read the FAQs or contact Dr. Peter Lin, FSA Program Director at [email protected]

Frequently Asked Questions (FAQ's)