B.S. in Economics and Data Science

Economics and Data Science (B.S.)

Economists explore how markets work—producing, distributing, and consuming goods and services—and they analyze how individuals, organizations, and nations manage and use resources, respond to incentives, and make choices about spending, investment, and policies. Data scientists manage, analyze, and visualize massive amounts of data to find patterns and derive knowledge and insights.

The Bachelor of Science in Economics and Data Science degree teaches students how to apply the concepts of economics and the powerful techniques of data science in order to understand economic events and trends, develop business and organizational strategies, predict potential outcomes, and make informed decisions.

In this interdisciplinary program you will learn from world-class faculty at Illinois Institute of Technology’s Stuart School of Business and College of Computing, and take courses in economics, business, data science, computer science, and applied math.

Graduates are prepared with STEM-oriented expertise and skill sets that enable them to solve complex challenges, increase efficiency, and lead data-driven decision-making in the business, government, and nonprofit sectors.

Through Illinois Tech’s one-of-a-kind Elevate program, you are guaranteed access to hands-on experiences—such as internships and group projects—where you connect your learning with real-world practice. You also receive a personalized plan and mentorship to guide your academic studies and build your career readiness.

Chicago is an international center for business and finance, with a diverse metro economy that is home to a growing array of tech companies. Illinois Tech’s connections provide you with access to internships, networking, and job opportunities in a variety of industries.

STEM-Designated Program

This is a STEM-designated program, and international graduates of the program are eligible to apply for an extension for Optional Practical Training, which allows selected students to stay and work in the United States for up to three years after graduation.
 

Program Overview

The Bachelor of Science in Economics and Data Science degree focuses on applying data science concepts in the economics domain. With a grounding in these two complementary disciplines, graduates are ready to use high-level computational techniques to gain valuable insights from data, predict trends, solve business problems, and help businesses and organizations become more efficient.

Career Opportunities

The B.S. in Economics and Data Science degree provides excellent preparation for a variety of job roles in the private sector, particularly at technology-focused or financial businesses, as well as in the nonprofit, government, and consulting sectors.

Overall, the employment outlook is very good for the roles listed below. Estimated median annual wages in 2022 and projected employment growth from 2022–32, as reported by the United States Bureau of Labor Statistics, are also shown below.

  • Data scientist or business intelligence analyst—median wages of $103,500; job growth of 35 percent (much faster than the average growth for all job categories)
  • Operations research analyst—median wages of $85,720; job growth of 23 percent (much faster than the average growth for all job categories)
  • For students who take appropriate elective courses in finance:
  • Economist—median wages of $113,940; job growth of six percent (faster than average)
    • Positions typically require a master’s degree. Interested students could consider the Accelerated Master’s Program co-terminal option, pairing this bachelor’s degree with the M.S. in Economics and Data Analytics or M.S. in Financial Economics degrees.

Other examples of potential job roles for graduates of this program include:

  • Quantitative research analyst
  • Financial data scientist
  • Health care economist
  • Policy analyst or researcher
  • Economic research analyst
  • Business continuity planner or consultant

The B.S. in Economics and Data Science degree requires a total of 126 credit hours, including 42 credit hours of economics requirements and electives, 21 credit hours of data science requirements and electives, 17 credit hours of mathematics requirements, and four credit hours of computer science requirements, as shown below. Courses are three credit hours each unless otherwise noted.
View course descriptions for: Business (BUS), Economics (ECON), Data Science (DS), Mathematics (MATH), Computer Science (CS), and Statistics (STAT).

Economics Requirements (33 credit hours)
These courses are required:
BUS 100—Introduction to Business and Economics
BUS 102—Introduction to Business Analytics
BUS 221—Business Statistics or MATH 225—Introductory Statistics
BUS 321—Analytics for Optimization
BUS 480—Strategic Management and Design Thinking
ECON 151—Microeconomics
ECON 152—Macroeconomics
ECON 311—Intermediate Microeconomics
ECON 312—Intermediate Macroeconomics
ECON 382—Business Economics
ECON 423—Economics of Capital Investments

Economics Electives (nine credit hours)
Choose three from the following courses:
BUS 210—Introduction to Accounting
BUS 211—Financial Accounting
BUS 212—Managerial Accounting
BUS 301—Organizational Behavior
BUS 305—Operation and Supply Chain Analytics
BUS 311—Strategic Cost Management
BUS 341—Business Law
BUS 361—Entrepreneurship
BUS 371—Marketing Fundamentals
BUS 452—International Finance
BUS 454—Investments
BUS 455—Corporate Finance
BUS 457—Financial Modeling
BUS 458—Financial Derivatives
BUS 472—New Product Development
BUS 473—Marketing Analytics
BUS 475—Sales Management and Analytics
BUS 476—Consumer Behavior
ECON 383—Sports Economics

Data Science Requirements (15 credit hours)
These courses are required:
DS 151—Introduction to Data Science
DS 261—Ethics and Privacy in Data Science
DS 451—Data Science Life Cycle
ECON 251—Introduction to Econometrics
MATH 474—Probability and Statistics or MATH 476—Statistics

Data Science Electives (six credit hours)
Choose one course from CS and one course from DS, MATH, or STAT:
CS 422—Data Mining
CS 430—Introduction to Algorithms
CS 484—Introduction to Machine Learning
CS 584—Machine Learning
DS 251—Mathematical Foundations for Data Science I
DS 351—Mathematical Foundations for Data Science II
MATH 350—Introduction to Computational Mathematics
MATH 380—Introduction to Mathematical Modeling
MATH 435—Linear Optimization
MATH 446—Introduction to Time Series
MATH 475—Probability
MATH 484—Regression
MATH 497—Special Problems
MATH 569—Statistical Learning
MATH 574—Bayesian Computational Statistics
STAT 514—Applied Computational Statistics for Analytics

Mathematics Requirements (17 credit hours)
These courses are required:
MATH 151—Calculus I (five credit hours)
MATH 152—Calculus II (five credit hours)
MATH 251—Multivariate and Vector Calculus (four credit hours)
MATH 332—Elementary Linear Algebra

Computer Science Requirements (four credit hours)
Choose one of the following two options:

  • CS 115—Object-Oriented Programming I (two credit hours) and CS 116—Object-Oriented Programming II (two credit hours)
  • or CS—201 Accelerated Introduction to Computer Science (four credit hours)

In addition to the economics, data science, mathematics, and computer science courses shown above, the requirements for this degree include 37 credit hours of Illinois Tech core curriculum requirements and five credit hours of free electives.

Admission to Illinois Tech is required to enroll in the B.S. in Economics and Data Science program. Current Illinois Tech students should consult their academic adviser to transfer into the program.

Featured Faculty

Meet your professors! Here are some of the faculty from Stuart School of Business and College of Computing who teach courses in this program.

John Twombly
Associate Dean for Undergraduate Affairs Director of Undergraduate Programs in Business Clinical Professor of Accounting and Finance Adjunct Faculty, Industrial Technology and Management
Robert Ellis
Associate Professor of Applied Mathematics
Ghazale Jafari Haddadian
Clinical Associate Professor of Operations and Energy Management
Ioan Raicu
Associate Professor of Computer Science Associate Program Director Master of Data Science
Priyanka Sharma
Associate Professor of Economics
Kai Shu
Gladwin Development Chair Assistant Professor of Computer Science
Alan Secor
Industry Assistant Professor of Public Administration
Despina Stasi
Associate Teaching Professor of Applied Mathematics
Xiaoyun "Aarn" Cao
Clinical Assistant Professor of Management
Binghui Wang
Assistant Professor of Computer Science
Sang Baum Kang
Assistant Director, Undergraduate Programs in Business Associate Professor of Finance
Ming Zhong, assistant professor of Applied Mathematics
Assistant Professor of Applied Mathematics

For More Information

College of Computing

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Stuart School of Business

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