Columbia University School of Professional Studies seeks candidates for the role of adjunct Lecturer for the Fall 2025 semester to teach the graduate-level course, Advanced Predictive Modeling Applications in the school’s highly ranked Master of Science degree program in Actuarial Science. Scholar-practitioners with relevant academic and industry experience are invited to apply.
Advanced Predictive Modeling Applications discusses Bayesian methods for estimating linear models. We discuss three methods for estimating the Bayesian posterior: grid approximation, quadratic approximation, and Markov Chain Monte Carlo (MCMC) methods. Bayesian methods are used to estimate linear regression models and generalized linear models. We also use Bayesian methods to estimate multilevel models, also known as linear mixed models. We also estimate linear mixed models using non-Bayesian methods. We learn how to build, estimate, and evaluate these models and how to select the best one.
This class covers most of the material of Exam MAS II of the Casualty Actuarial Society. This is a core class of the Actuarial Science program.
Serving as an adjunct Lecturer provides an outstanding opportunity to educate and mentor students aspiring to a career in Actuarial Science related fields as well as to form a rewarding professional relationship with Columbia University’s world-class faculty. Candidates should have a demonstrated understanding of academic and
applied trends that are driving best practice in the field.ResponsibilitiesAttend all class sessions (class generally meets once per week for up to 2 hours), conduct the lectures, and lead classroom administration.Lead preparation of course materials including the oversight of the course Canvas webpage (learning management system), weekly presentations, development of class readings, etc. Part‐time Lecturers who are new to SPS must complete Canvas training. Monitor student concerns and inquiries; conduct office hours.Evaluation and grading of student assessments and work.The Lecturer role is outlined in more detail here. Class Days and Times
Mondays and Wednesdays; 2:40pm to 3:55pm EST
