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The Master of Science in Statistics and Data Science at Yale University is a rigorous, theory-grounded, and application-oriented graduate program offered through the Graduate School of Arts and Sciences (GSAS). This STEM-designated program provides students with a strong foundation in statistical theory, data analysis, machine learning, and computational methods, preparing them for data-intensive careers in academia, research, industry, and public service.
The program is ideal for students with solid mathematical and computational backgrounds seeking to bridge advanced statistics with real-world problem-solving across fields like health, policy, economics, technology, and social sciences.
Program Format & Duration
Full-time, on-campus program (New Haven, CT)
Duration: Typically 2 years
Administered by the Department of Statistics and Data Science
STEM-designated (eligible for OPT extension for international students)
Fall intake only
No thesis required, but includes comprehensive coursework and optional research
Core Curriculum Components
The program combines rigorous mathematical and statistical training with practical data science tools and applications.
Core Course Areas
Statistical Foundations
Probability Theory
Theory of Statistics
Linear Models
Statistical Inference
Bayesian Statistics
Computational & Data Science
Machine Learning
Data Mining
Algorithms for Data Science
Computational Statistics using R/Python
Data Visualization and Communication
Electives & Interdisciplinary Options
Students can take electives across Yale in fields like:
Computer Science
Economics
Public Health
Political Science
Genetics/Bioinformatics
Capstone / Project Work
Though not mandatory, students can pursue independent research, data-driven projects, or participate in faculty-led initiatives
Emphasis on real-world datasets, reproducibility, and statistical rigor
Yale’s S&DS program places a strong emphasis on hands-on analytical work, interdisciplinary collaboration, and research-driven inquiry.
Capstone Project / Thesis
Projects may be research-oriented or problem-solving based with data from real industries or academic fields
Students work under faculty mentorship and may collaborate with external organizations or Yale-affiliated research centers
Research Opportunities
Students may engage with Yale research centers such as:
Center for Research Computing
Yale Institute for Network Science
Yale School of Public Health (for biostatistics and epidemiology research)
Interdisciplinary Engagement
The flexible curriculum allows students to pursue electives across Yale’s schools including:
School of Management
School of the Environment
Jackson School of Global Affairs
Department of Computer Science
Graduates of Yale’s Statistics and Data Science Master’s program are highly competitive in the global job market and for doctoral programs.
Career Outcomes
Common job titles include:
Data Scientist
Statistician
Quantitative Analyst
AI/ML Engineer
Biostatistician
Policy Data Analyst
Research Scientist (Social Sciences, Healthcare, or Economics)
Top Employers
Yale S&DS graduates have gone on to:
Google, Meta, Amazon, Microsoft
Boston Consulting Group, McKinsey, and data-focused startups
Healthcare and biotech companies
Federal agencies, NGOs, and research institutes
Further Study
Graduates also pursue:
PhDs in Statistics, Biostatistics, or Data Science
Interdisciplinary doctoral research in areas like Public Health, Economics, or Computational Biology
Joint research programs or funded fellowships at academic and policy institutions
Online Application & Deadline: Apply online via Yale GSAS by December 1 (11:59 PM ET) for the M.S. program. Bachelor’s Degree: Hold a bachelor’s degree (U.S. 4-year or international equivalent, including most 3-year degrees) before matriculation.Transcripts: Upload unofficial transcripts from all postsecondary institutions; official and certified English translations only if admitted.Standardized Tests: GRE general and subject scores are optional and may be submitted at your discretion.English Proficiency: Submit TOEFL/IELTS scores unless you have a bachelor’s degree from a school where instruction was in English for at least 3 years.Quantitative Background: Demonstrate strong preparation in advanced calculus, linear algebra, probability theory, and mathematical statistics. Letters of Recommendation: Provide academic references (number unspecified, but strong recommendation letters are important). Statement of Academic Purpose: Include a description of your academic record, motivation for graduate study, and quantitative preparation. Residency Requirement: Complete at least three semesters of GSAS enrollment for M.S.; part-time study allowed with extended residency.Course Load: Complete twelve graduate-term courses (with at least two honors grades) including core probability, statistics, theory, and data science methods.Three‑Year Bachelor’s Degrees: A U.S.-equivalent bachelor’s degree is required; Yale accepts three-year degrees from recognized institutions as long as they meet this equivalency, with no special steps needed upon application .WES Evaluation: Applicants must submit official academic transcripts directly from each institution, and while WES or other credential evaluations are optional, they cannot replace official transcriptsData 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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Yale University
