Enter the data science and machine learning workforce as a competent data professional with skills in machine learning, predictive analytics, applied statistics, big data technologies, and cloud computing.

The M.S. in Data Science is a joint program run by the CIS Department and the Mathematics Department and meets the data demands of today and tomorrow.

Data science is the study of data and how individuals and organizations can extract value from data to make accurate predictions and actionable decisions. The ability to do this in the face of massive quantities of data and data sets requires a cross-disciplinary knowledge and the application of a range of algorithms and software tools to utilize that knowledge.   

The graduates of the M.S. in Data Science degree program will be equipped with the statistical and computational prowess to meet the demands of the industry. They will possess the agility and adaptability to grow as data science professionals as the field evolves. 

• Interdisciplinary Program: Data Science science is the integration of several academic fields of study, bringing together the traditional disciplines of business analytics (modeling, optimization, simulation, decision support systems), statistics, computer science (machine learning, pattern recognition, artificial intelligence), and management.  
• Competency for Data Demands of Today and Tomorrow: Gain a comprehensive understanding of business data needs today and tomorrow, how to extract information from large and complex datasets, how to realize the potential and variety of a complex analysis, and how to provide results and conclusions that create value and actionable knowledge. 
• Scholar-Practitioner Faculty: Study with professors who are recognized specialists in the field and who mentor you. They actively engage in the field and present on their areas of expertise locally and globally. 
• Demand for Data Science Professionals: Information economy has an immediate shortage of data science professionals who have the background, knowledge, and understanding of how to make sense of the data and what questions to ask of the data to make it relevant and usable.
• Fully Online: Complete your degree fully online-anywhere/anytime.

This is a joint program between SIHSS and SEMS.

Degree Requirements and Courses

View Printable Course Sheet

Course requirements:

• STAT5100 Fundamentals of Data Science
• INFS5110/STAT5110 Data Visualization
• INFS6244 Database Systems for Data Science
• INFS6241 Big Data Technologies
• STAT6050 Statistics for Data Science 
• STAT6486/INFS6486 Data Modeling and Simulation
• INFS7140 Python for Data Analysis
• INFS6482/STAT6482 Applied Machine Learning
• INFS6720 Data Mining
• INFS7100/STAT7100 Data Science Capstone

Degree Program Learning Outcomes

Program Objectives

• Demonstrate knowledge of data science  techniques utilized in decision making.
• Apply principles of data science to the analysis of problems in a variety of industries.
• Apply appropriate algorithms to develop machine learning solutions.
• Formulate problems and assess the data science needs of an organization.
• Use appropriate techniques and tools to collect, prepare, and analyze large datasets to solve data science tasks.
• Select, apply, and evaluate appropriate computational and statistical algorithms and models to provide solutions to data related problems.
• Interpret and communicate analysis outcomes in oral, visual, and in written form to technical and non-technical professionals.

Career Preparation

Upon completion of the degree, graduates can seek roles as data scientists, machine learning engineers, data engineers, operations analysts, data analysts, and artificial intelligence engineers.  

Data scientists are hired across multiple industries, the following industries have the highest levels of demand for data scientists:

Industry Annual Mean Salaries

• Computer Systems Design and Related Services  $111,490
• Management of Companies and Enterprises  $107,980
• Management, Scientific, and Technical Consulting Services  $100,800
• Scientific Research and Development Services  $109,610
• Insurance Carriers  $104,670

Source: Bureau of Labor Statistics, U.S. Department of Labor, Occupational Employment and Wage Statistics at https://www.bls.gov/oes/current/oes152098.htm (visited April 27, 2021).

Operations Research Analyst 

The U.S. Bureau of Labor Statistics projects a 25% growth in U.S. employment for operations research analysts from 2019 to 20219, much faster than the average for all occupations. Some employers prefer to hire applicants with a master’s degree. Typical degree areas include “business, operations research, management science, analytics, mathematics, engineering, computer science, or another technical or quantitative field.”

The May 2020 median annual wages

• For operations research analysts $86,200
• In the top industries for operations research analysts
  • federal government $119,720
  • manufacturing $94,340
  • management of companies and enterprises $86,280
  • professional, scientific, and technical services $85,950

Source: Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, Operations Research Analysts, at https://www.bls.gov/ooh/math/operations-research-analysts.htm (visited April 14, 2021).

Admissions, Tuition and Scholarship Information

• Prospective Students should have an undergraduate GPA of 3.0 and above with a degree in statistics, computer science, information systems, mathematics, financial mathematics, software engineering, actuarial science, or related fields.
• Students from other fields are welcome to apply, but must take two prerequisite courses at the undergraduate level, one in statistics and one in Python programming, before beginning the MS Data Science program.  The prerequisite courses include:
  • STAT 2110 Statistics OR ASCI 2010 Fundamentals of Actuarial Science
  • INFS 3240 Python Programming
• Comparable prerequisite courses transferred from another university may be accepted upon review.
• 4+1 accelerated prospective students are encouraged to take the prerequisite courses as open electives to prepare them to begin the Data Science program.
• Click here for tuition information.

Contact Us

Natalya G. Bromall, Ph.D.
CIS Graduate Program Director
Associate Professor of Computer and Information Systems 
Department of Computer and Information Systems
Email: bromall@rmu.edu

Heather H. Elfen, Ph.D.
Department Head, Mathematics
Associate Professor of Mathematics
Department of Mathematics
Email: elfen@rmu.edu
412-397-3533 phone

Jamie L. Pinchot, D.Sc.
Department Head, Computer and Information Systems
Professor of Computer and Information Systems
Department of Computer and Information Systems
Email: pinchot@rmu.edu