Full-Time Visiting Assistant Professor, Applied Statistics
Job Description
Position Description
New York University’s Steinhardt School of Culture, Education, and Human Development is accepting applications for a non-tenure track Visiting Assistant Professor position, Applied Statistics, to begin September 2023. The appointed faculty member will be part of the Department of Applied Statistics, Social Science, and Humanities (ASH). The clinical professor will teach statistics and statistical consulting classes for graduate students. The strong candidate will experience applying methods to a substantive discipline. All courses are intended for practitioners in social science and related fields, so a commitment to creative, engaging content and course materials is required. There may be advisement and related administrative opportunities and expectations. The faculty member will be expected to teach the equivalent of 6 classes per academic year. We are committed to substantially increasing the proportion of our faculty from historically underrepresented groups as we strive to create the most intellectually diverse, inclusive, and equitable institution that we can, and especially encourage candidates from historically underrepresented groups to apply.
Responsibilities
Teach graduate students with a 3:3 teaching / administrative load; participate in course development, advising, and program management. There is a possibility of buying out of up to 3 courses for a candidate with grant funding.
In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is $85,000-$125,000. New York University considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills, internal peer equity, as well as market and organizational considerations when extending an offer.
Qualifications
Requirements: Graduate degree in statistics or related field. Experience teaching statistics to graduate students.
Preferred skills: Experience developing statistical software and interactive learning tools. Experience scaling up classes by automating grading of assignments. Experience with statistical consulting.
