The Applied Data Science concentration is designed for students who want rigorous training in statistical modeling, computation, and data science, with greater flexibility to connect these tools to domain-specific applications in areas such as biology, economics, political science, psychology, and other data-driven fields.
How do I know if this program is right for me?
Any WashU undergraduate student with a background in a quantitative field, such as the social sciences or biological sciences, is eligible to apply. Prospective students are encouraged to consult their academic advisors as early as possible—and no later than their junior year—to ensure they can prepare adequately for the accelerated program.
Before applying, you should have introductory-level coursework in calculus, linear algebra, and statistics. Completion of an undergraduate statistics course, such as SDS 3020 or equivalent, is needed. Students who need additional preparation in calculus and/or matrix algebra may take a bridge course offered by SDS to strengthen their background.
The Applied Data Science concentration is designed for students interested in quantitative social science or life science applications. Students majoring in STEM fields may choose either the Applied Data Science concentration or the Statistics concentration within the same master's degree program. Students with backgrounds in the humanities are also welcome but should first ensure they have completed introductory coursework in mathematics and statistics. Once these prerequisites are met, they are well prepared to pursue the Applied Data Science concentration.
WashU offers several data science–related master’s programs, but they differ in academic home, focus, and intended preparation.
· The McKelvey School of Engineering’s MS in Engineering Data Analytics and Statistics: designed for students interested in gaining advanced expertise in the use and application of cutting-edge software and analytical tools to collect, analyze, model and optimize data. It is recommended that incoming students earn an undergraduate degree in engineering or another STEM-related degree.
· The School of Medicine’s MS in Biomedical Data Science & AI and MS in Biostatistics & Data Science offered through the Institute for Informatics, Data Science & Biostatistics: designed for students interested in biomedical data science, biostatistics, and health data.
· The Olin Business School’s MS in Business Analytics: with a focus on analytics to business decision-making, including concentrations on accounting, fintech, healthcare, and supply chain, with training that combines technical skills, problem-solving, and applied business experience.
By comparison, this degree is housed in Arts & Sciences and is centered on statistics and data science as a discipline. It emphasizes statistical reasoning, modeling, inference, computation, uncertainty quantification, and principled analysis across a broad range of applications. The data science concentration is open to students from a wide range of academic backgrounds who want to add rigorous statistical and data science training to their primary area of expertise.
The two concentrations within the master's program share a common core while serving different educational goals. The Statistics concentration emphasizes statistical theory and methodology with a stronger mathematical foundation, whereas the Applied Data Science concentration focuses on practical statistical and data science tools for solving problems across a broad range of application domains.
All courses are conducted in person to promote effective teaching and learning.
Students should first speak with their department liaison* (if available) to discuss how the accelerated pathway fits their undergraduate major, academic goals, and course plan. Alternatively, they may contact the SDS Director of the Master’s Program at SDSMastersDirector@wustl.edu for guidance.
*Department Liaisons have been assigned for the Department of Biology (Himadri Pakrasi, pakrasi@wustl.edu), the Department of Psychological & Brain Sciences (Joshua Jackson, j.jackson@wustl.edu), and for the Department of Political Science (Ted Enamorado, ted@wustl.edu).
What is the program like?
Students complete 30 units of coursework that combine core training with elective flexibility. In the Applied Data Science concentration, required courses include probability and statistical inference, linear statistical models, statistical computation, Python for data science, and practical training in statistics. Students select 18 units of electives, allowing them to explore areas such as machine learning, data mining, artificial intelligence, causal inference, and other advanced topics in statistics and data science. Subject to program requirements, students may also choose electives from their own disciplines, enabling them to integrate statistical and data science training with their primary area of interest.
Course requirements and elective options are listed in detail in the Bulletin.
Yes. The program provides the statistical and computational foundation needed to understand, evaluate, and use AI and machine learning methods responsibly. Core coursework in statistical modeling, inference, computation, and Python prepares students to work with modern data-driven tools.
Students can further develop AI and machine learning expertise through electives offered across WashU, such as statistical learning, Bayesian statistics, deep reinforcement learning, natural language processing, large language models, and applications of deep neural networks. Available courses and electives are listed in the University Bulletin.
Yes. Students apply statistical and data science methods to real problems through course-based projects, programming assignments, and practical data analysis. The required Practical Training in Statistics course also provides an opportunity to connect classroom learning with applied experience.
Students who would like a more substantial research experience may pursue the optional thesis pathway, working independently with a faculty advisor on a data science research project. The Bulletin provides additional details about practical training and the thesis option.
The program is actively expanding internship and experiential learning opportunities through partnerships with employers in the St. Louis region and beyond. While internship is not a program component, students are encouraged and supported in pursuing internships in statistics, data science, artificial intelligence, and analytics throughout the program.
Past students of the Master’s program in Statistics have secured internships with organizations such as Bayer, Mastercard, Boeing, Reinsurance Group of America, and Schnucks. In addition, the required “Practical Training in Statistics” course reinforces the program's emphasis on applying statistical and data science knowledge to real-world problems and preparing students for professional practice.
How will this program help my career?
As a new concentration, we do not yet have historical career outcome data for our graduates. A useful reference is the Occupational Outlook Handbook for Data Scientists published by the U.S. Bureau of Labor Statistics. Graduates of master's programs in applied data science commonly pursue careers as data scientists, data analysts, senior data analysts, business intelligence analysts, decision scientists, analytics consultants, quantitative analysts, research data scientists, healthcare data analysts, and bioinformatics data analysts.
According to the U.S. Bureau of Labor Statistics' Occupational Outlook Handbook for Data Scientists, the median annual salary for data scientists was $112,590 in 2024. In addition, a recent article posted at Brandeis Online reports that between September 2024 and September 2025, U.S. employers posted more than 88,000 job openings for master's-level professionals in data science, statistics, and operations research. These positions had a median salary of $140,200. Actual total compensation varies considerably depending on factors such as the employer, industry, geographic location, level of experience, and specific job responsibilities.
This degree prepares students for careers in AI, analytics, and data science by building a strong foundation in statistics, computation, and data-driven problem solving. Students learn how to model complex data, evaluate uncertainty, use modern computational tools, and communicate results clearly. These skills are essential for roles that involve machine learning, predictive modeling, statistical analysis, experimentation, and decision-making with data.
The program’s emphasis on statistical reasoning helps students understand not only how to apply data science and AI methods, but also when they are appropriate, how to interpret their results, and how to assess their reliability. Graduates are prepared to work in a range of settings where rigorous data analysis is needed, including technology, healthcare, finance, government, research, and other data-intensive fields.
Employers value the combination of statistical expertise, computational ability, and practical problem-solving developed through this degree. Students learn to manage and analyze complex data, build and evaluate statistical and machine learning models, quantify uncertainty, and use modern programming and computational tools.
Equally important, students learn to translate real-world questions into appropriate analytical approaches, assess the reliability and limitations of their results, and communicate findings clearly to both technical and nontechnical audiences. These transferable skills prepare graduates to contribute effectively across industries and in roles related to AI, analytics, data science, research, and statistical modeling.
What should I know before entering the program?
Submit an online application through WashU Graduate Admissions. Applicants should provide a statement of purpose, resume or CV, transcripts from all undergraduate and graduate institutions, and 2-3 letters of recommendation. GRE scores are not required, though applicants may submit them if they wish. Applicants whose prior education does not meet WashU’s English-language proficiency criteria must also submit qualifying test scores.
For current deadlines, application requirements, and the online application portal, visit the Department of Statistics and Data Science’s Graduate Application Information page.
The application deadline for the general MA program is April 10. Applications are reviewed in batches, so applicants are encouraged to apply early for earlier consideration.
For WashU undergraduates applying to the accelerated BA/MA track, the application deadline is March 15. Applicants should check the Graduate Application Information page for the most current deadlines and application details.
WashU undergraduates in the accelerated BA/MA pathway may apply a minimum of 9 and a maximum of 12 units of eligible 4000- or 5000-level coursework completed during their undergraduate studies toward the MA degree, subject to program approval. These credits can help students complete the master’s degree in one additional year after earning their bachelor’s degree.
The program does not require a specific minimum GPA for admission. Applications are reviewed holistically, with attention to academic preparation, quantitative coursework, statement of purpose, recommendations, and relevant experience.
Once enrolled, students must maintain a B (3.0) or better GPA in graduate coursework. Students interested in the optional thesis pathway must maintain a 3.5 cumulative GPA during their first 18 units of program coursework. See the program requirements for details.
Students in the accelerated BA/MA pathway officially become graduate students after completing all undergraduate degree requirements and matriculating into the MA program. Although eligible graduate-level credits may be taken during the undergraduate years, students remain undergraduates until their bachelor’s degree has been awarded.
Accelerated BA/MA students begin the graduate program in the academic year immediately following graduation.
Yes. The accelerated BA/MA pathway is designed to allow qualified WashU undergraduates to complete the MA degree in one additional academic year after earning their bachelor’s degree, for a total of approximately five years of study.
Careful planning is essential. Students should consult with their department liaison or the SDS Director of the Master’s Program during their sophomore or junior year to plan eligible coursework. Students should verify their eligibility by the beginning of the fall semester of their senior year, before the add/drop deadline.
Program Financials
Because our program takes just one year (after your undergraduate education) rather than the 1.5 to 2 years typical elsewhere, you save one-third to one-half of the total cost right off the top — before the tuition discount even applies. The savings easily reach $50,000 or more.
Through the completion of your BA or BS, you continue to pay undergraduate tuition. Graduate tuition rates begin in your fifth year, when you enroll as a master's student.
WashU undergraduate students are eligible for a 25% tuition discount in their fifth year, when enrolled as master's students in the accelerated program.
The current tuition for the master's program is $69,190 for one academic year, before any discount for WashU undergraduates. Additional costs include a mandatory student health and wellness fee of $350 per semester, health insurance, housing, and other daily living expenses. Total costs for the fifth year — after you complete your BA or BS at WashU — vary with lifestyle, but $80,000 is a reasonable ballpark figure.
This is a self-funded program. At this time, there are no scholarships available.