Business Analytics Careers
The program is designed for students with a passion for getting the most out of data. These careers position students for success in an increasingly data-centric business world. Graduates will make robust use of industry standard tools such as R and Python throughout the entire value chain of business analytics, from strategy formulation to data collection, data formulation, data visualization, and analysis - to aid businesses with decision making.
Top Growth Careers
From the team behind the #10 ranked Management Information Systems program nationally by USA Today, the MS in Business Analytics program is designed to meet the rising national and international demand of businesses for professionals who can collect, analyze, and interpret the avalanche of data created in the context of economic activity.
Typical job titles include: Business Intelligence Analyst, Business Data Analyst, Digital Media Analyst, Credit Risk Analyst, Web Analytics Specialist, Economic Analyst, Data Analytics Manager, Customer Analytics, Digital Analytics and Insights, Corporate Banking Analyst, and others.
Here you will find information regarding outcome data collected by our Office of Cooperative Education and Career Services, as well as median salaries for every program at RIT. You can also view RIT's Careers and Employment Trends page, which includes both Job Outlook and a summary of career outcomes for each’s year graduating class from RIT.
Saunders Advisory Boards
All Saunders College graduate programs are enhanced by the experience and leadership of our corporate partnerships through the Saunders Industry Advisory Boards. The Management Information Systems (MIS) Advisory Board is a vital resource for the MS in Business Analytics program, bringing expertise and guidance from global companies to assist Saunders in delivering the highest quality curricula that maintains an applied focus, and includes what employers are looking for in graduates of Saunders College.
Business Analytics profesionals can help bring data to life through data visualizations. These can include static as well as animated graphics that can help display data dynamically and provide charts that utilize more than two data points. Some examples include: