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Master of Science 

Business Analytics

Program of Study


In UAlbany's 30-credit MS in Business Analytics curriculum, you will learn a variety of analytics methods from predictive and text analytics to social network analytics and optimization. You’ll gain practical experience applying analytical models by working with industry-standard software tools such as Python, R and SAS to develop business solutions.

Required Courses (27 credits)

  • Business Analytics and Data Mining
  • Databases and Business Intelligence
  • Topics in Business Analytics and Text Mining
  • Forecasting and Panel Data Analysis
  • Decision Analytics and Optimization
  • Design of Experiments & Data Quality, Security and Privacy
  • Business Dynamics: Simulation Modeling for Decision-Making or approved elective
  • Analytics and Visualization
  • Selected Topics in Marketing: Analytics for Strategic Marketing or approved elective

Research Requirement (3 credits)

  • Research Seminar in Information Systems and Business Analytics

Additional Information

See the Graduate Bulletin for details.

For more information, contact Eliot Rich at [email protected] or 518-956-8320.


In the Research Seminar course, you will study intensive academic and information systems and business analytics research. This course culminates in your own applied research or consulting project. 

You will have the opportunity to demonstrate your competence in business analytics applications while gaining valuable experience developing, executing, summarizing and presenting findings to diverse audiences.

A group of students studying in the UAlbany Massry Center for Business
Career Outcomes

From business analytics to data science, with a master’s in business analytics from UAlbany you will have the expertise to pursue a high-demand career in finance, health care, marketing, retail and technology. 

Potential job titles for an MS degree in business analytics:

  • Business Intelligence Analyst
  • Marketing Analyst
  • Financial Analyst
  • Data Scientist
  • Operations Research Analyst
  • Business Analytics Consultant
A professional giving a business presentation in a business meeting.

International Students

This degree is designated as a STEM program. International students maintaining F-1 status are allowed to apply for up to 12 months of post-completion Optional Practical Training (OPT) following completion/graduation from their degree program. Currently, this degree program is also designated by the Department of Homeland Security (DHS) as an eligible degree for the F-1 STEM OPT work authorization extension; students who secure qualifying employment may be eligible to apply for the STEM OPT extension for a cumulative total of up to 36 months of F-1 OPT work authorization.

Admissions Requirements

 Departmental Assistantship Consideration

  • Fall: April 1
  • Spring: Not available
  • Summer: Not available

No Departmental Assistantship Consideration

  • Fall: June 15
  • Spring: Not available
  • Summer: Not available
Required Application Materials
  • Transcripts from all schools attended
  • Three letters of recommendation
  • GRE/GMAT scores (Note: The GRE/GMAT requirement has been waived for Fall 2024)
  • Statement of Purpose


Special Notes

Admission consideration requires students to have previous quantitative analysis, Excel and programming experience. Students entering the program are expected to have completed the following UAlbany courses or their equivalents:

  • Quantitative Analysis for Business
  • Advanced Excel with Visual Basic for Applications
  • Advanced Programming

Applicants may be offered conditional admission and allowed to complete these admission requirements prior to the start of the degree program.

Student Learning Objectives

Learning objectives that UAlbany students are expected to attain through their course of study within their academic program.

Master of Science

At the end of the degree program, you will be able to: 

  • Identify business problems and the appropriate data required to study them. 
  • Collect, clean and structure data in a format suitable for conducting analysis. 
  • Evaluate a wide variety of analytics methods, including predictive analytics, text analytics, social network analytics and optimization. 
  • Apply the appropriate analytical model using a suitable package from statistical software like Python, R and SAS to solve business problems. 
  • Link business strategies to inferences derived from data. 
  • Summarize key points and create succinct presentations to explain their analysis to C-level executives. 
  • Work independently and in teams to identify superior business opportunities.