Open Positions

Faculty Positions

Professional-Track Faculty Position in the Department of Statistics and Data Science

The Department of Statistics and Data Science (SDS) at The University of Texas at Austin invites applications for the Director of the MS Program in Statistics, with appointment at the rank of Associate or Full Professor of Instruction. SDS is looking forward to an expansion of its MS program through an integrated 4+1 BS/MS sequence for our rapidly growing Statistics and Data Science major. The Director of the MS Program will help lead this initiative alongside the chair of the department, shaping curriculum, advising, admissions, and the long-term academic vision of the program, while also teaching classes at the undergraduate and MS level. The anticipated start date for the position is either January 1, 2027 or August 16, 2027.

Applications will be reviewed until the position is filled, with all applications received by August 17, 2026 receiving full consideration. Assuming the position continues to remain open, applications received after August 17, but before November 16, 2026, will continue to be considered.

Tenured/Tenure-Track Faculty Positions in the Department of Statistics and Data Science

The Department of Statistics and Data Science (SDS) at The University of Texas at Austin invites applications for tenured or tenure-track faculty positions, at any rank, to begin in August 2027. We seek exceptional scholars whose work advances our ability to learn from data, whether by directly addressing important empirical questions in a chosen area of application, or by deepening the foundations of statistical inference and learning.

We are particularly interested in four broad directions. First, we seek candidates in applied statistics, scientific machine learning, or AI for science: methodologists embedded deeply enough in another field that they help shape its scientific questions and build new data-analysis methods in response. The field may be any area of the natural, biomedical, computational, engineering, or social sciences. For such candidates, we regard publication in the leading venues of their chosen field as central evidence of impact, on equal footing with publication in statistics and machine-learning venues. No matter the area, the candidate's record should exhibit methodological advances that statisticians and machine-learning researchers would recognize as such, even if they first appeared in a domain journal.

Second, we welcome research in causal inference, experimental design, and related areas concerned with learning from interventions and designing informative studies. This includes foundational and applied work on how interventions are identified and evaluated, how evidence generalizes across settings, and how experiments and other data-collection strategies can be designed to answer important questions.

Third, we seek scholars working on statistical theory, including the foundations of machine learning and AI. We are interested in fundamental questions about inference, uncertainty, information, learning, robustness, computation, and decision-making. We value theoretical and computational work that provides new understanding of (or new broad capabilities for) statistics, machine learning, and AI, whether or not it is tied to an immediate application.

Fourth, we welcome work that creates broadly useful new computational tools for data-analytic practice, such as statistical computing environments and languages, probabilistic programming systems, scalable inference software, and interactive or AI-assisted tools for data analysis. For such candidates, widespread adoption of their tools by researchers and practitioners is evidence of impact on equal footing with publication.

Candidates should have a doctoral degree in statistics, biostatistics, computer science, machine learning, applied mathematics, or a closely related discipline by August 2027.

Candidates for a tenure-track Assistant Professor position are evaluated based on their potential for developing an impactful research program and for becoming excellent in teaching, mentoring, and service.

Candidates for a tenured Associate or Full Professor position are expected to exhibit a strong independent program of externally funded research along with established records of excellence in teaching, mentoring, and service. Further details about this position and instructions for submitting an application are available here.

Applications will be reviewed until the position is filled, with all applications received by November 23, 2026 receiving full consideration. 

Professional-Track Faculty Position in the Department of Statistics and Data Science

The Department of Statistics and Data Science (SDS) at The University of Texas at Austin invites applications for professional-track faculty positions at the rank of Assistant, Associate, or Full Professor of Instruction. SDS is the newest and fastest growing department in the College of Natural Sciences and is dedicated to delivering high-quality, innovative education in statistics and data science across the university. Our programs include an undergraduate major and minor in Statistics and Data Science, an M.S. and Ph.D. in Statistics, an undergraduate certificate in Applied Statistical Modeling, and an online M.S. in Data Science offered in collaboration with the Department of Computer Science. SDS is internationally recognized for excellence in statistical methodology and theory, applied statistics, data science, biostatistics, and machine learning.

Applications will be reviewed until the position is filled, with all applications received by November 30, 2026 receiving full consideration. 

Graduate Student Positions 

Teaching Assistant 

The Department of Statistics and Data Science regularly hires The University of Texas at Austin graduate students to serve as teaching assistants for our undergraduate courses. Applicants for these positions should have a strong background in statistics and/or data science. 

• To apply for a Teaching Assistant position, please fill out this survey.

Undergraduate Student Positions

Undergraduate Course Assistants

The Department of Statistics and Data Science regularly hires The University of Texas at Austin undergraduate students who have completed specific courses to serve as an undergraduate teaching assistant for the course.  In addition, the department employs undergraduate student assistants to support the main office operations.

• There are no open positions at this time.