"Part-time Lecturer, Causal Inference"

NYU Paris is seeking a part-time lecturer to teach an undergraduate course in Data Science, Causal Inference. The course is held at NYU's academic center in Paris and is offered to undergraduate students. Language of instruction: English. Teaching commences in January 2026; courses meet for 2.5 hours per week for a 14.5-week term. Lecturers will teach an additional recitation session for 1.5 hours per week. Instructors should be prepared to teach in-person and remotely via Zoom if required.

Course Description: Prerequisite: Intro to Data Science. Teaches fundamentals of reasoning about causality using empirical data. Introduces the counterfactual framework and various approaches for causal inferences from data. Addresses data generation, interpretation, and hands-on implementation using R or Python. Includes theoretical and applied problem sets.

About NYU and NYU Paris: Founded in 1831, New York University is a large private university with campuses in New York, Abu Dhabi, and Shanghai, and global academic centers. NYU Paris offers immersive study programs for students earning credits towards their degrees. Visit NYU Paris for more information.

Candidates must have a Ph.D. in Data Science or a related field, and two to three years of relevant teaching experience. The appointee will have full responsibility for teaching and coordinating the course to a small group of undergraduate students from NYU campuses in New York, Abu Dhabi, or Shanghai, studying at NYU Paris for one semester. Classes take place at the Academic Centre in Paris. Candidates must be eligible to work in France.

Applications must include: (1) a cover letter, (2) C.V., and (3) course outline or synopsis. Apply online through Interfolio at apply.interfolio.com/165229. Current NYU Paris faculty are encouraged to apply. NYU Paris is committed to equity, diversity, and social inclusion.