Knowledge of, or ability to learn several commonly applied statistical methods such as hierarchical regression models with random intercepts and slopes, parametric survival models including accelerated failure time models, effect modification and moderation methods, understanding of the basic principles of risk adjustment within the CMS framework, econometric modeling for cost variables with highly skewed distributions, generalized linear models including repeated measures analysis, machine learning approaches such as XGBoost, Explainable Boosting Machines (EBMs), random forests, random survival forests, cluster analysis, latent class analysis, and other classification approaches. Demonstrated excellence in at least one area of expertise, which may include coordinating studies; statistical methodology such as missing data, survival analysis, statistical genetics, or informatics; statistical computing; database design (e.g., expertise in RedCAP or MySQL); graphical techniques (e.g., expertise in Illustrator).