Part-time Lecturer, Causal Inference

Job description

Description NYU Paris is seeking a part-time lecturer to teach an expected undergraduate course in Data Science, Causal Inference. The course is held at NYU academic center in Paris and is offered to undergraduate students. Language of instruction: English: Teaching commences in September 2026; courses meet for 2.5 hours per week for a 14.5 week term.Lecturers will be expected to teach an additional recitation session for 1.5 hours per week. Causal Inference: Prerequisite: Intro to Data Science: Teaches the fundamentals of how to reason about causality and make causal determinations using empirical data. Introduces the counterfactual framework of causal inference and then considers a variety of approaches, starting with the most basic experimental designs to more complex observational methods, for making inferences about causal relationships from the data. Addresses questions about data generation and interpretation and provides hands-on implementation of causal inference techniques with real data sets. Problem sets will contain a mixture of both theoretical and applied questions in order to reinforce key concepts. Examines theoretical concepts and their applications; uses R or Pyt...