Financial Technology and Analytics Master's Degree
Today's financial industry is driven by technology, making it essential for professionals to have expertise in areas such as financial technology, data science, and advanced analytical modeling.
At Stevens, financial analysts combine their programming skills with talents in data analysis and statistics to design innovative solutions to finance problems. Financial Analysts also use excellent business and communication skills to assess client needs and make recommendations to executive teams.
The Master's in Financial Technology and Analytics program is designed for STEM students who are looking to pursue careers in the financial industry. The program covers a range of topics in financial technology and data science, including financial technology, blockchain technologies and decentralized finance, digital payment technologies and trends, applied statistics with applications in finance, introduction to financial risk management, and time series with applications to finance or advanced financial econometrics.
Graduates of our program will be well-equipped to lead financial technology and data science teams in both start-ups and established financial firms. They will be able to build advanced analytical models, make enterprise data analytics decisions, and orchestrate advanced financial systems technology resources in a cloud-based data-driven distributed environment. They will also have the skills to construct innovative financial products and apply their expertise to a range of general financial services analytics.
Our faculty are experts in the field and are constantly exploring new concepts in machine learning, data modeling, and optimization in finance. Students will have the opportunity to learn from these professionals and work with the data analysis and visualization tools used on Wall Street in our state-of-the-art financial labs.
The Technology and Financial Analytics program has two concentrations:
• The Financial Data Science concentration focuses on Data Analysis and Machine Learning applications to Finance.
• The Financial Technology concentration is focused on the newest technology emerging in recent years.
As a student, you are required to choose one of the concentrations, and additionally customize your degree with a set of four elective courses, including the chance to pursue a structured specialization tailored to your career interests. A close collaboration between you and your faculty advisor will help you select the right classes for your future.
These 9 credits are required for both concentrations. The students will learn fundamental data techniques, SQL, as well as machine learning techniques. FA582 and FE513 are first semester classes, while the capstone FA800 is to be completed in the last semester.
The students in the M.Sc. in Financial Technology and Analytics are required to choose one of the following two concentrations. Please expand to see the courses in each concentration.
Capstone Course or Master's Thesis
Students are required to complete a significant project as part of their Master experience. They can choose to complete the FA 800 Project in Financial Analytics during their final semester. They would work in teams often on projects offered by our industry partners.
Alternatively, the students may complete a thesis option. This means completing FA900 over two consecutive semesters. The project is going to be individual and will prepare the students in case they wish to pursue a Ph.D. degree in Data Science.
Ideal candidates for the program will have a strong background in statistics, mathematics, physics, engineering or a related discipline, or will have several years' experience working in finance with an interest in exploring these disciplines in great depth.
Full-time applications to the Financial Analytics program are accepted in three distinct cycles. To be considered for admission, all materials must be submitted by the deadline.
Included in admission offer
Part-time applications to this program are accepted on a rolling basis.
Admission to the Financial Technology and Analytics master’s program is competitive. To be considered for this program, your application must include the following.
You may apply to the Financial Technologies and Analytics program without any work experience, but students without work experience will need excellent academic credentials from their undergraduate work, with a degree in statistics, mathematics, physics, engineering, or another math or science discipline.
For finance professionals interested in working in an analyst capacity, work experience is preferred. To keep up with the technical nature of coursework, computer science and statistics skills also are required.
A list of general Stevens admissions criteria is available at the Office of Graduate Academics.