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To learn more about Drexel LeBow’s master’s programs, students are encouraged to attend an information session or request additional information.
We are not currently accepting applications for this program. If you have any questions, please contact the LeBow Graduate Enrollment team at lebowgradenroll@drexel.edu.
The First of Its Kind in the Philadelphia Region
The MS in Economics and Data Science at Drexel University is an interdisciplinary, STEM-designated degree that combines advanced economic analysis with data science, quantitative methods and computing. Offered collaboratively by the School of Economics in the LeBow College of Business and the Nick Howley College of Engineering and Computing, the program prepares students to analyze complex data, apply economic reasoning and generate insights for data-driven environments across business, government and academia.
#6
Edurank, 2025
Top 10%
IDEAS/RePEc, August 2025
Why Study Economics and Data Science at Drexel LeBow?
Drexel’s MS in Economics and Data Science combines advanced economic analysis with data science and computing, giving students an interdisciplinary skill set for solving complex, data-driven problems. Through internship opportunities, applied coursework and real-world data analysis, students gain valuable work experience while completing their degree.
Who Should Apply?
The MS in Economics and Data Science is designed for recent graduates and professionals who want to build advanced data skills to support career advancement, a career change or future doctoral study.
This program may be a good fit if you:
- Have an academic background in economics, business, data science, computer science, mathematics, statistics or finance
- Work in consulting, analytics, finance, banking or government and want to expand your quantitative and data science skills
- Want to combine economic analysis with data science and computing to prepare for data-driven roles
- Plan to pursue doctoral study and want to strengthen your advanced quantitative and data analysis skills
Inside the MS in Economics and Data Science Curriculum
MS in Economics and Data Science students develop a strong foundation in economics and data science, building skills in economic modeling, statistical analysis, econometrics and quantitative reasoning. Coursework also introduces data processing and machine learning applications, helping students strengthen their ability to analyze complex datasets and solve problems in economic contexts.
The curriculum emphasizes hands-on, applied learning. You’ll work on projects involving data acquisition, preprocessing and analysis while drawing on perspectives from economics, data science and computing. This interdisciplinary approach helps you develop the technical and analytical skills to approach complex problems from multiple perspectives.
You’ll graduate prepared to:
- Advanced Economic Analysis: Students will demonstrate the ability to apply advanced economic theories and quantitative methods to analyze complex economic problems, utilizing econometric models and data analysis techniques to derive meaningful insights and policy implications.
- Critical Thinking and Problem Solving: Graduates will develop strong critical thinking and ethical reasoning skills, enabling them to evaluate economic policies and their societal impacts, propose evidence-based solutions, and effectively address real-world economic challenges.
- Research and Communication Skills: Students will acquire the ability to conduct rigorous economic research, including formulating research questions, analyzing empirical data, and interpreting results. They will also be skilled in communicating complex economic concepts clearly and persuasively to diverse audiences.
- Develop Proficiency in Quantitative Analysis: Graduates will demonstrate a solid understanding of advanced mathematical and statistical concepts, enabling them to apply techniques such as econometrics, data analysis, and machine learning to interpret complex datasets and derive meaningful insights.
I realized if I wanted to take things up a notch, I’d need to go back to graduate school. After graduation, I landed my dream job offer: working as a data engineer for Facebook. I’m now working with rich marketplace data on a global scale.
Ananth Bevinahally ’20
Data Engineer
Learning Through Experience
Experiential learning is woven throughout every LeBow graduate program. You’ll apply classroom concepts through hands-on projects, learn from faculty with industry expertise and engage with opportunities that connect your studies to professional practice.
93%
One year out, LeBow's class of 2025
96%
One year out, LeBow's class of 2025
MS in Economics and Data Science Career Outcomes
Graduates of the MS in Economics and Data Science can pursue opportunities that draw on their combined knowledge of economics, quantitative analysis and data science. Potential career paths span data analytics, finance, consulting and public policy, with roles in both the public and private sectors. The program also provides preparation for students interested in doctoral study in economics, data science and related disciplines.
Potential roles include:
- Data Analyst
- Data Scientist
- Economic Consultant
- Research and teaching roles in higher education
Common Questions About the MS in Economics and Data Science
- Do I need a background in economics or data science for a master’s in economics and data science?
Not necessarily. Drexel’s MS in Economics and Data Science is designed for students from a range of academic backgrounds, including economics, business, data science, computer science, mathematics, statistics and finance. The program may also be a fit for professionals working in consulting, analytics, finance, banking or government who want to expand their quantitative and data science skills.
- How is a master’s in economics and data science different from a master’s in data science?
The Master’s in economics provides the theoretical knowledge needed to understand the data analysis at a much deeper level. Economics provides the questions. Data science provides a method to manipulate large data sets to help answer those questions.
- What is the difference between econometrics and data science?
Econometrics can address the question of causality based on economic theory. Data science provides an array of tools for finding relationships, but stops short of a deep understanding.