In the 21st century, data is everywhere—and the ability to harness, interpret, and act on data has become a defining skill in almost every field. At the forefront of this revolution is Carnegie Mellon University (CMU), a global leader in statistics, machine learning, and data science. Known for its rigorous academics, innovative research, and cross-disciplinary collaboration, CMU prepares students not just to work with data—but to lead the future of analytics and artificial intelligence.
A History of Innovation and Excellence
Founded in 1900 in Pittsburgh, Pennsylvania, Carnegie Mellon has always been associated with technological advancement and intellectual rigor. Its Department of Statistics & Data Science, part of the Dietrich College of Humanities and Social Sciences, plays a key role in the university’s reputation as a trailblazer in computation, artificial intelligence, and data analytics.
What distinguishes CMU is its ability to integrate statistical thinking with cutting-edge computation, machine learning, and real-world application. From its earliest contributions to Bayesian modeling and decision theory to today’s breakthroughs in AI ethics and high-dimensional data analysis, CMU has continuously helped shape the future of statistics.
World-Class Academic Programs
Carnegie Mellon offers a suite of programs designed to serve students at every level—from undergraduates just beginning their data journey to doctoral candidates conducting groundbreaking research.
Undergraduate Programs
CMU offers several pathways for undergraduates interested in statistics and data science, including:
- Bachelor of Science in Statistics
- Bachelor of Science in Statistics and Machine Learning (a joint program with the School of Computer Science)
- Minor in Statistics
The curriculum emphasizes both theoretical rigor and applied experience. Students study core topics like:
- Probability theory
- Statistical inference
- Regression and multivariate analysis
- Machine learning
- Programming in R, Python, and other statistical tools
CMU’s undergraduate statistics students are encouraged to participate in faculty research, industry internships, and interdisciplinary projects that prepare them for immediate impact in fields such as finance, tech, healthcare, and government.
Graduate Programs
CMU’s graduate programs are known for their academic rigor and flexibility. They include:
- Master of Statistical Practice (MSP)
- Ph.D. in Statistics
- Ph.D. in Statistics and Machine Learning
Master of Statistical Practice (MSP)
This 12-month professional master’s program is ideal for students seeking applied experience. It emphasizes real-world consulting, communication, and data storytelling, preparing graduates for careers as data scientists, business analysts, or research specialists.
Ph.D. Programs
CMU’s Ph.D. offerings attract top students from around the globe. The traditional Ph.D. in Statistics focuses on statistical theory and applications, while the Ph.D. in Statistics and Machine Learning is a joint program with the Machine Learning Department—bridging probabilistic modeling, computational algorithms, and theoretical foundations.
These programs emphasize research excellence, and students are encouraged to publish in top journals, present at conferences, and collaborate across disciplines.
Faculty Leadership and Interdisciplinary Expertise
CMU’s statistics faculty are internationally recognized leaders in:
- Bayesian inference
- Statistical computing
- Time series and spatial modeling
- High-dimensional data analysis
- Causal inference
- Machine learning and artificial intelligence
Notably, the department includes faculty with appointments in Computer Science, Machine Learning, Public Policy, Biological Sciences, and Engineering, fostering a uniquely interdisciplinary culture.
CMU faculty are known for their accessibility and mentorship. They actively involve students in research and often work on high-impact projects funded by organizations like the NSF, NIH, and DARPA.
Research That Changes the World
The Department of Statistics & Data Science is at the core of some of the most transformative research in modern data science. Its interdisciplinary focus makes it a hub for innovation in fields ranging from genetics to robotics to social science.
Research Strengths Include:
- Bayesian and computational statistics: CMU has been a pioneer in Bayesian thinking and modern Monte Carlo methods.
- Machine learning and AI: Faculty regularly collaborate with the Machine Learning Department, one of the first of its kind in the world.
- Ethics and fairness in algorithms: Research at CMU addresses bias, transparency, and accountability in automated decision-making.
- Health and life sciences: CMU statisticians contribute to biomedical research, clinical trials, and public health analytics.
- Public policy and social data: Through partnerships with policy institutes and government agencies, CMU applies data to improve education, justice, and equity.
Students are integral to this research ecosystem. Many graduate students work on collaborative, interdisciplinary projects and gain experience in publishing, consulting, and policy impact.
Strong Industry and Research Partnerships
CMU’s location in Pittsburgh—a rising tech and innovation hub—means it’s closely connected to industry leaders in AI, robotics, and data analytics. The university has strong partnerships with:
- Microsoft
- Amazon
- Facebook (Meta)
- Uber ATG
- The RAND Corporation
- UPMC (University of Pittsburgh Medical Center)
These partnerships translate into abundant opportunities for internships, co-ops, and job placements. CMU’s career support and alumni network ensure that graduates are well-positioned to succeed in competitive roles across the globe.
The Center for Statistics and Data Science
The department also collaborates closely with the Heinz College of Information Systems and Public Policy, the School of Computer Science, and the Delphi Research Group, which has gained international attention for its work on real-time pandemic forecasting and public health data analysis.
The university’s Statistics & Data Science Center fosters education, innovation, and cross-disciplinary research. It hosts workshops, seminars, and symposia featuring leaders in the field, and provides collaborative spaces where students and faculty work on data challenges of societal importance.
Student Experience and Campus Life
CMU offers a dynamic and intellectually vibrant student life. Statistics students can participate in:
- DataFest – An annual data analysis competition
- Statistical Consulting Center – Real-world consulting projects with organizations
- Data Science Club – Hackathons, coding sessions, and speaker events
- Interdisciplinary research teams tackling problems in AI, robotics, neuroscience, and more
The university fosters a collaborative environment where students from various programs come together to solve pressing problems using data.
Diversity, Equity, and Inclusion
CMU is deeply committed to creating an inclusive academic culture. The department supports diversity in all its forms and works actively to reduce barriers for underrepresented groups in STEM. Scholarships, mentorship programs, and affinity groups help create a supportive and inclusive environment for all students.
Ethical responsibility is a core part of the curriculum, and students are encouraged to reflect on the societal implications of their work—from privacy issues to algorithmic bias.
