• Work on all steps of data management; including preprocessing, manipulation, visualization, analysis, interpretation and presentation. • Perform statistical analysis, including ANOVA, regression, structural equation modeling, multilevel modeling, longitudinal modeling (with panel data or intensive repeated measures), nonlinear modeling, differential equation modeling, dyadic data analysis, factor analysis, time series analysis, cluster analysis, latent class analysis, latent profile analysis, and data mining• Use both Bayesian and frequentist approaches to perform statistical analysis• Derive new statistical methods to test novel research hypotheses• Command statistical software suites, including R, SAS, Mplus, Stata, SPSS, JAGS WinBUGS, and STAN• Create reports, presentations, and scientific articles to articulate meaningful insights for both technical and non-technical audiences. • Taught research methods and statistical analysis at both the undergraduate and gradute level• Mentored and guided research projects for Master's and doctoral students