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.

The MS in Data Analytics Engineering is a multidisciplinary degree program in the Volgenau School of Engineering, and is designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making. Students study topics such as data mining, information technology, statistical modeling, predictive analytics, optimization, risk analysis, and data visualization. It is aimed at students who wish to become data scientists and analysts in finance, marketing, operations, business/government intelligence and other information intensive groups generating and consuming large amounts of data.

Students are strongly encouraged to meet with their academic advisor during their first semester and design an approved plan of study. Students should seek out their advisor when questions arise and when their plan of study needs to be revised. Any changes to the plan of study are to be approved by the DAEN advisor.

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.
• Résumé.
• 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.

Tuition fee-2 years$58,000

Total fee-2 years$1,04,000