Assistant Professor, Data Science and Statistics

Assistant Professor, Data Science and Statistics

Lawrence University of Wisconsin, a selective undergraduate liberal arts college and conservatory of music located in Appleton, Wisconsin invites applications for a tenure-track Assistant Professor of Data Science and Statistics to begin September 1, 2027. We seek candidates who will contribute to our growing program, which includes a new Data Science and Statistics major. Candidates must have a Ph.D. in statistics, biostatistics, data science, or a closely related field prior to the time of appointment (9/1/2027);

ABDis acceptable for selection. Candidates should demonstrate potential for teaching a variety of undergraduate statistics and data science courses, and expect to participate in Lawrence's flagship First Year Studies program on rotation. Primary duties include: teaching two undergraduate courses in each of Lawrence's three ten-week terms, grading, advising and mentoring students; conducting research; leading occasional tutorials, supervising independent study projects and internships;

assisting in curricular planning; and related departmental and institutional service. The successful candidate will be the third statistics and data science faculty member in the Department of Mathematics, Statistics, and Computer Science. Additional information about our curriculum and faculty can be found at https://(Use the "Apply for this Job" box below)..

Candidates should submit the following: (1) a cover letter describing their interest in this position, (2) a curriculum vitae, (3) a statement of teaching explaining their pedagogical methods and teaching experiences, (4) a statement describing their scholarly activities, interests, and future plans, (5) names and email addresses for three references who can be contacted for letters of recommendation at a later stage in the process (at least one of whom can attest specifically to teaching).

In their teaching statement, candidates are encouraged to discuss their experiences and ideas for teaching courses involving data analysis and computational tools. Candidates should also discuss how they will foster an inclusive and supportive learning environment for all students. In their scholarship statement, candidates are encouraged to discuss their experiences or ideas for incorporating undergraduate students in their research.

We will begin reviewing applications on October 2, 2026. For further information, please contact Andrew Sage, the chair of the search committee (sagea).