The masters in data analytics engineering is designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making. Topics cover data mining, information technology, statistical models, predictive analytics, optimization, risk analysis, and data visualization. Aimed at students who wish to become data scientists and analysts in finance, marketing, operations, business intelligence, and other information-intensive groups generating and consuming large amounts of data, the program also has wider applications, including concentrations in digital forensics, financial engineering, and business analytics.
Please see the University Catalog for complete information on program requirements and policies. Additional specifications may apply.
Applicants must have completed a baccalaureate degree from a regionally accredited program with a reputation for high academic standards and an earned GPA of 3.00 or better in their 60 highest-level credits. While no specific undergraduate degree is required, a background in engineering, business, computer science, statistics, mathematics, or information technology, is desirable, or alternatively strong work experience with data or analytics may be used.
For each of the concentrations there are additional admission requirements. These are listed below in the descriptions of the individual concentrations.
In addition to fulfilling Mason’s admission requirements for graduate study, applicants must provide:
- Two letters of recommendation, preferably from academic references or references in industry or government who are familiar with the applicant’s professional or academic accomplishments.
- Detailed statement of career goals and professional aspirations.
- Completed self-evaluation form.
- If the applicant’s native language is not English, proof of English competency with a minimum TOEFL score of 575 for the paper-based exam or 230 for the computer-based exam.
Graduates with a master’s degree in data analytics engineering are part of a new class of engineers that deploy an interdisciplinary approach of statistical science, computer science, systems analytics, and another field of study such as business, operations research, geoscience, or bioscience. These specialized engineers build the structures that work to contain and organize gigantic fields of data so that it can be used to predict consumer behaviors, social trends such as extremism, disease threats, and factors influencing and influenced by climate change. Mason’s graduates benefit from our extensive history in sociological research, information technology, and global studies, which lends this program its unique strength. The employment outlook for this field is new and growing rapidly.