Financial Analytics, MS
Program at a Glance
Program
Financial Analytics, MS
Format
Online, Hybrid
Total Units
30
Requirements
No GMAT or
GRE Required
Spring ’25 Early Application Deadline
November 10
Program Overview
Golden Gate University is located at the nexus of finance and technology in San Francisco’s business district. As the finance industry rapidly invents new paradigms in the face of economic change, GGU prepares students to be leaders in the global business world. The Masters of Science in Financial Analytics degree will equip you with the business analytics skills you need to address the challenges of today’s technology-intensive finance industry.
The MS in Financial Analytics is a specialized, technical program that provides in-depth exposure to principles and practices of corporate finance and business analytics. You’ll learn programming, data analysis, business valuation and financial modeling. You’ll leave the program with a highly developed and practiced ability to make strategic decisions using the latest tools in technology, data analysis, business and finance. This program is a STEM-designated degree program.
Our hands-on faculty are leading practitioners in the fields of business, finance, and technology from the Bay Area and beyond. Our current roster of adjunct faculty hold day jobs at Wells Fargo, J.P. Morgan, Facebook, BridgeBio, RGB Spectrum, and B. Riley FBR, Inc.
Admission Requirements
- Applicants should hold a bachelor’s degree from a regionally accredited U.S. institution or the equivalent from a recognized foreign institution (outside the United State), and provide official transcripts.
- All applicants will need to submit a Statement of Purpose (SOP) and a resume.
- For applicants with a GPA under 3.0, the Statement of Purpose should address the circumstances that led to the applicant’s academic performance, what has changed, and why they think they’ll be more successful now.
- Applicants whose native language is not English must meet the English Language Proficiency Admission Requirements.
Proficiency Requirements
Math Proficiency
Intermediate Algebra (Math 20); See Graduate Mathematics Proficiency Requirement for more information.
Writing Proficiency
Students are expected to possess proficiency in writing to ensure they can be successful in their course of study. Students may meet this requirement by satisfying one of the screening criteria listed under Graduate Writing Proficiency Requirement.
Curriculum
The Master of Science in Financial Analytics requires completion of 6 units in the foundation program and 30 units of advanced program coursework, with a cumulative grade-point average of 3.00 or better in courses taken at Golden Gate University that are applicable to the program’s requirements. For further information regarding graduation requirements, see Degree Requirements for Graduate Programs. Courses carry three semester units of credit unless otherwise noted.
All course prerequisites must be satisfied prior to enrolling in a given course and are indicated in the the course description for each course. Individual foundation program courses may be waived if students have previously completed comparable courses at a regionally accredited college or university. Students may enroll in advanced program courses before they have completed the entire foundation program (provided they have met any course prerequisites) but must complete the foundation program by the time that they have enrolled in 12 units in the advanced program.
Select any ACCTG, ECON, FI, or MSBA 300/400-level course, which may include FI 497 Internship: Finance.
Learning Outcomes
Graduates of the MS in the Financial Analytics degree program will have the knowledge and skills to:
- Evaluate and explain financial decisions regarding the firm’s investment and long- and short-term financing strategies by applying financial theory, quantitative decision-making tools, and analytical methods.
- Apply economic analysis to the firm’s decision-making, considering the impact of markets, institutions, and international trends on these decisions.
- Define and measure business and financial risk. Describe the relationship between risk and return, and distinguish between expected and required returns. Explain how risk affects the valuation of real and financial assets, and describe techniques for managing risk.
- Interpret and analyze individual business problems using data, selecting the best analytic approach and appropriate tools for extracting value from the data available. Use visual outcomes of analytics to communicate effective messages and recommendations for management teams.
