- 30 credit hours with on-campus and online degree options: complete in 18 months or at your own pace.
- Choose from 10 tracks, including Public Affairs, Investigative Journalism, Environmental Science, Finance, or Cybersecurity.
- Spring or fall admissions; GRE scores and bachelor’s degree in technical field not required.
- Project-based curriculum culminates in Practicum applying skills and creativity to real-world solutions.
Learn the skills to meet growing demand for advanced data scientists—in the area with the highest US concentration of data science jobs—in a program where you can start from any level, choose your own specialty, and execute real-world projects demonstrating job readiness.
Design Your Own Data Science Niche
Choose from primary coursework tracks including
- Applied Public Affairs
- Business Analytics
- Computer Science
- Environmental Science
- International Economic Relations
- Investigative Journalism
- Microeconomic Analysis
- Specialized Methods
Those preferring the Online MS Program can choose tracks in Business Analytics or Specialized Methods. While pursuing their primary track, students will master both the theoretical knowledge and practical skills used by data scientists in academia, industry, and government.
Core courses such as Statistical Machine Learning, Data Science, and Statistical Programming in R will train students to clean, process, visualize, and archive modern datasets, including text, imagery, and biometric data, apply machine learning algorithms to real data, and use the mathematical and statistical language of data scientists, leading to the DATA-793 Practicum, working directly with faculty and other researchers' ongoing projects.
Knowledgeable Faculty Dedicated to Your Success
Courses are taught by the same knowledgeable, innovative, and widely published professors who teach our master of arts, master of science, and undergraduate courses. You will learn the theories of data science and practical skills from respected experts in the field: Data Science Faculty.
Faculty research interests include
- Jeff Gill: Bayesian modeling and data analysis (decision theory, testing, model selection, elicited priors) to questions in general social science quantitative methodology, political behavior and institutions
- Elizabeth Malloy: Applied biostatistics, especially smoothing methods for estimating non-linear exposure-response relationships in different contexts, such as survival models and functional linear models.
- Zois Boukouvalas: Development of interpretable machine learning models and algorithms for the analysis of big multi-modal data, by combining aspects from information geometry, mathematical statistics, and numerical optimization, e.g., with biomedical images for studying psychiatric illnesses, social and linguistics data for understanding political and social trends.
- Maria Barouti: Machine learning and nuumerical optimization, e.g., data mining by identifying patterns in big data sets and developing feature selection algorithms.
- Michael Robinson: Intersections between signal processing, the art of collecting and analyzing measurements, and topology, the study of abstract notions of space.
- Michael Alonzo: Software development with satellite and drone imagery (plus other geospatial tools) to study forests and land cover change.
Make a Difference in the Nation's Capital
Consistently ranked as one of the best cities for job seekers, Washington, DC, offers data scientists unparalleled access to private– and public–sector opportunities. AU's campus is minutes from industry giants such as Deloitte Consulting, Amazon, Booz Allen Hamilton, National Institutes of Health, BNY Mellon, Cambridge Associates, Lockheed Martin, and the Peace Corps. Our graduates start with a foot in the door, thanks to the Data Science Center and university's institutional relationships with government agencies, locally-based companies, and nonprofit organizations.
The Bureau of Labor Statistics ranks DC as the area having the nation's highest concentration of data science positions and annual mean wage in surrounding areas of $122,740.
Respected Positions in a Growing Field
The US Bureau of Labor Statistics projects a 36% increase in data science jobs from 2021 to 2031 — with DC having the nation's highest concentration of data science positions. Forbes and Glassdoor consistently rank Data Scientist at or near the top of all professions for job-satisfaction and median base salary at $120,000. There are limitless applications for the skills you will gain from an MS in Data Science.
Recent graduates now have positions with
- Booz Allen Hamilton
- Gitlab BV
- Federation of American Scientists
- LNL DATA LLC
- Management Insight Technologies
- National Association of Counties
- National Institutes of Health
- National Rural Electric Cooperative Association
- Operation Pathways
- Precision Strategies
- Samuel DeWitt Proctor Conference Inc.
- New York State Senate
- Third Way
- Tidal Wave Strategies Inc.
- US Census Bureau, Department of Labor, General Services Administration, Senate, and House of Representatives
Marketable skills include how to
- Use Data Science methods to create ethical, data-driven solutions for real problems in diverse fields
- Integrate specialty domain knowledge with acumen in mathematics, statistics, and computing
- Develop reproducible analyses using modern statistical/programming methods and tools
- Collect, clean, and organize large amounts of data from open data sites, through APIs, via web scraping or from SQL-based databases
- Create meaningful visualizations and graphics of quantitative and categorical data
- Apply appropriate statistical methods to build, analyze, test, and validate models of large data sets
- Apply advanced regressions methods for multivariate regression
- Develop machine learning solutions using statistical and quantitative methods
- Build and deploy web-based apps for interactive analysis
- Communicate complex ideas on data and solutions to diverse audiences orally and in writing
- Conduct ethical reviews of data sources and applications to identify potential issues and solutions
- Collaborate as a member of a team to complete projects on time to the desired quality
- Code proficiently with R, Tidyverse, R Shiny, R Markdown, R Studio, Python, HTML, CSS, SQL
See more about our outcomes and graduation data.
Explore our MS in Data Science
The program is open to all students with a bachelor's degree from an accredited institution that have a cumulative grade point average of at least a 3.00 (on a 4.00 scale). Students without sufficient mathematical background as determined by the program directors may be required to complete a mathematical boot camp prior to starting the program.
You can find information about application deadlines here.