The admissions committee seeks candidates who are a good fit for the MSA program. Indications of a good fit include some of the following criteria::
- Professional work experience: Competitive candidates must have at least three years of full-time work experience, and must be employed at the time of enrollment. The years of experience doesn’t have to be with the same employer.
- Strong academic background: A competitive undergraduate or graduate GPA compliments a strong application. In addition to the GPA, a strong GRE/GMAT score is also required. The GRE/GMAT can be waived after a comprehensive review of an applicant’s file. Please know, GRE/GMAT scores are not waived based on years of employment. The waivers granted are based on academic performance.
- Statistics competency: Applicants must have completed at least one Statistics course with a grade of B or better.
- Purpose: A well written statement of purpose about how this analytics degree will help your organization.
- Organizational support: Support from current employer for access and mentorship with a business problem and large data set is required to complete the capstone project graduation requirement.
- Potential for contributing to the learning experience: The admissions committee evaluates candidates on their knowledge, experiences and intellectual curiosity to determine whether they will add value to the classroom discussion and contribute to the learning of other seasoned professionals.
- Ability to work in a team environment: Analytics is not a task one person can do on their own. It takes a group of people. To meet that expectation, MSA looks for candidates who understand how to work effectively in teams.
- Commitment to completing the program: Strong candidates display a professional demeanor and have a proven track record of successfully starting and completing endeavors.
- Ability to balance the MSA program, career responsibilities and personal life: Successful applicants have strong time management and planning skills that will help them handle multiple and competing demands on their time.