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The Master of Science in Data Science (MSDS) at the University of Chicago is a rigorous, full-time, in-person program that delivers deep training in the theory and application of data science. Administered by the Department of Computer Science in collaboration with the Committee on Data Science, the program emphasizes the foundations of data analytics, statistical modeling, machine learning, and domain-specific applications.
Located in the heart of Chicago, the program is ideal for students with strong quantitative and coding backgrounds who want to become leaders in data-driven research, industry innovation, or advanced academic study.
Program Format & Duration
Full-time, in-person, cohort-based
Duration: 12–18 months (3–4 quarters)
Starts: Autumn Quarter
STEM-designated (OPT eligible for international students)
GRE optional
Core Curriculum Components
The program provides a comprehensive curriculum in both theoretical foundations and practical tools, allowing students to develop a deep understanding of how data is acquired, stored, processed, and analyzed to inform decision-making.
Core Courses (required)
Students complete courses in the following foundational areas:
Data Science Fundamentals
Introduction to Data Science
Statistical Analysis & Inference
Applied Linear Algebra
Data Engineering Platforms
Programming & Tools
Python for Data Science
Data Visualization
Databases and Cloud Computing
Machine Learning & AI
Supervised and Unsupervised Learning
Deep Learning and Neural Networks
Natural Language Processing
Capstone Project
A practical, team-based project that runs over multiple quarters
Focused on applying machine learning and data science methods to real-world problems
Electives
Students can tailor their degree through electives in areas such as:
Time Series Analysis
Reinforcement Learning
Bayesian Inference
Causal Inference
Fairness and Ethics in Data Science
Financial Analytics
Health Analytics
Advanced AI Systems
The UChicago MSDS program emphasizes hands-on, project-based learning in all components of the curriculum, encouraging students to apply their skills in real-world environments and interdisciplinary contexts.
Capstone Project
Spans two to three quarters, culminating in a professional presentation
Students work in teams on data projects for real clients or research groups
Topics may involve finance, policy, social science, medicine, or tech applications
Supervised by faculty and industry mentors
Industry Engagement
Frequent seminars and workshops with industry leaders and alumni
Strong ties with companies like JPMorgan Chase, Morningstar, AbbVie, and Meta
Located in Chicago’s innovation ecosystem, providing access to internship and full-time opportunities
Research Opportunities
Students may collaborate with UChicago labs like:
Center for Data and Computing (CDAC)
Harris School of Public Policy
Booth School of Business
UChicago Medicine
Some students convert capstone projects into publishable research
Graduates of the UChicago MSDS program are prepared to tackle complex data problems in both industry and academia, equipped with strong foundations in mathematics, computing, and critical analysis.
Career Outcomes
Graduates typically pursue roles such as:
Top Employers
Further Study
Some graduates continue into:
Salary Overview-
Top Employers-
Geographic Placement-
Industry Sectors-
Career Growth and Progression-
What This Means for You-
Transcripts: Upload unofficial transcripts for all postsecondary institutions during application, and submit official copies (with sealed academic records and degree conferral) only if admitted.Letters of Recommendation: Provide two recommenders (at least one work-based preferred) via online portal, with submission allowed post-application.Candidate Statement: Submit a personal academic statement (≤1,000 words) clearly addressing goals and program fit.Résumé/CV: Include a current résumé highlighting relevant experience, skills, and achievements.Programming Supplement: Upload a PDF (max 2 pages) of R or Python code demonstrating data ingestion, wrangling, functions, analysis, and visualization. Virtual Portfolio: Record one required (~1:30 min) and one optional video responding to application prompts.English Proficiency (International): Provide TOEFL ≥ 102 or IELTS ≥ 7 (no subscore minimum), unless eligible for a waiver. Application Fee: Pay the $90 non-refundable application fee (fee waivers available via the Physical Sciences Division policy). Standardized Tests: GRE/GMAT are not required and may optionally be submitted.Deadline: Submit a complete application by June 23, 2025 to be considered for autumn admission (online or in-person, full-/part-time). Three‑Year Bachelor’s Degrees: The program requires a U.S.-equivalent bachelor’s degree, and while three-year degrees may be considered, if you're uncertain you should confirm equivalency before applyingWES Evaluation: Official academic transcripts must be sent directly from the institution and WES or other credential evaluations are not accepted in lieu of these, though optional for additional context Data AnalystData ScientistBusiness AnalystStatisticianStatistical ProgrammerSAS ProgrammerMachine Learning EngineerDeep Learning EngineerAI ResearcherData EngineerBI DeveloperData ArchitectAnalytics ConsultantAdvisory ConsultantQuantitative AnalystRisk AnalystOperations AnalystMarketing AnalystResearch ScientistInsights AnalystForecasting AnalystHealthcare Data AnalystFinancial Data AnalystProduct Analyst
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