Assistant Professor of Statistics & Data Science
Content + Source + Freshness • 15 Dec 2025 • 95% confidence
Offer value
Medium value given the established institution, but with less information on institutional support for faculty and expected salaries.
- Tenure-track role with opportunities for academic growth
- Engagement with diverse student populations
- Ambiguous salary structure to clarify
- Focus on teaching and research responsibilities
Pros
- Tenure-track position with the potential for professional growth
- Opportunity to teach and conduct research in a reputable setting
- Engagement with a diverse student population
Cons
- Ambiguous salary information and benefits
- Variable workload across different campuses may vary
- Less emphasis on cutting-edge research compared to peers
Who it's for
Mid-level / Experienced • On-site with a focus on teaching and research
Good fit
- Academics holding relevant degrees in Statistics
- Professionals passionate about teaching and mentorship
- Researchers interested in contributing to student success
Not recommended for
- Candidates without advanced qualifications
- Those looking for purely research roles
- Individuals preferring fully remote working options
Motivation fit
Key skills
About the job
The Department of Statistics & Data Science at Carnegie Mellon University (www.stat.cmu.edu) invites applications for a tenure track position at the rank of Assistant Professor starting in Fall 2026. The Department seeks strong candidates in all areas of statistics and data science, as well as related interdisciplinary fields. Potential areas of interest include but are not limited to computational finance, statistical theory, physical sciences and statistical computing. Excellent candidates with other research interests will also be considered and are strongly encouraged to apply.
Applications received by December 1st, 2025 are guaranteed to receive full consideration.
Carnegie Mellon Statistics & Data Science is world-renowned for the significance of its contributions to statistical theory and practice and for its outstanding interdisciplinary applied research. Faculty in the department are engaged in a wide range of theoretical, methodological and collaborative research. Current research by our faculty is helping to make fundamental advances in causal inference, neuroscience, cosmology, networks, finance, genetics/genomics, public policy, high-dimensional inference, sports analytics, and theory and methods at the intersection of statistics and machine learning.
Collaboration, both within the Department and across the university, is a core value of the Department and a hallmark of the research work of our faculty. The Department boasts a very friendly and energetic working environment, and is dedicated to fostering, mentoring and supporting its junior faculty.
The Department is also widely recognized for advancing the teaching of Statistics and Data Science and for the excellence of our undergraduate program, with large numbers of majors and popular joint programs in statistics and machine learning and statistics and economics. We also have two successful Master’s programs (Applied Data Science, Computational Finance) and a thriving Ph.D. program that attract exceptional students from around the world.
PhD (or equivalent international degree) or enrolled in PhD (or equivalent international degree generating program) at the time of application. Candidates will be expected to complete their PhD or equivalent degree no later than the start date of the appointment (August 2026).
To apply for the position, interested candidates must include a cover letter, a complete curriculum vitae, a research statement, a statement of teaching interests, and the names and contact information (email addresses) for writers of at least three letters of recommendation.
Applications, including all letters of recommendation, should be complete by December 1, 2025. Review of applications will begin December 1, 2025; the position will remain open until filled.
Carnegie Mellon University is an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information. Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders.
