Computational Decision Science and Operations Research (M.S.)

Discover the best decision-making methods within a problem’s constraints, and identify efficiencies to operate more effectively. This program meets the growing demand for computationally proficient decision scientists and operations researchers.

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Learn diverse techniques used by decision scientists and analysts to improve decision-making, including simulations, mathematical optimization, data analysis, statistics, neural networks, expert systems, and decision analysis. The program is research focused and offers hands-on experience with the real-world problems and ties to industry.

Take courses in applied mathematics, computer science, business, and engineering to maximize your ability to help organizations improve decision-making. Learn the most cutting-edge, sophisticated approaches—advanced analytics methods, algorithms, and machine learning—to meet the growing need for computationally sophisticated decision scientists and operations research professionals.

Program Overview

Courses in applied mathematics, computer science, business, and engineering maximize your ability to help organizations improve decision-making. Learn cutting-edge, sophisticated approaches—advanced analytics methods, algorithms, and machine learning—to meet the growing need for computationally sophisticated decision scientists and operations research professionals.

Career Opportunities

Decision scientists and analysts use diverse techniques to improve decision-making, including simulations, mathematical optimization, data analysis, statistics, neural networks, expert systems, and decision analysis in a broad range of areas. The U.S. Bureau of Labor Statistics estimates a much faster than average growth in operations analysts jobs from 2018–2028.

  • Operations research analyst
  • Logistician
  • Management analyst
  • Market research analyst
  • Economist

Students with bachelor of science degrees in mathematics, computer science, industrial engineering, electrical and computer engineering, mechanical engineering, and business, or related areas, with a minimum cumulative GPA of at least 3.0/4.0, will be considered.

Prospective students should have knowledge of linear algebra, discrete mathematics, probability and statistics, and programming.

A statement of objectives and a curriculum vitae must be submitted.

Two letters of recommendation are required.

GRE scores must meet Illinois Tech’s institutional requirements.

Strong applicants with holes in their academic background might be admitted with a requirement to take additional prerequisite courses.

Additional Information

Admission to CDSOR

What Is CDSOR?

Computational Decision Science

Demand for Operations Research Analysts

Faculty Research and Projects

Network Design Challenge

Rising Expert