As a principal statistician at NORC, Stas serves in leading statistical and analytical roles on projects and proposals. He develops complex sampling designs, statistical weights, imputation schemes, and provides internal statistical consulting on advanced statistical methods such as mixed models, structural equations with latent variables, and quasi-experimental inference with observational data.

Stas is very active in the data science community at NORC. He contributes to strengthening NORC expertise in reproducible workflows, statistical computing platforms comprising multiple statistical packages and code development tools that work together effectively, and applications of advanced computational methods such as Bayesian Markov chain Monte Carlo estimation of complex statistical models and machine learning.

Prior to joining NORC, Stas worked at Abt Associates at levels ranging from Senior Sampling Statistician to Principal Scientist. He was a short-term consultant to the World Bank Group and an Assistant Professor of Statistics at University of Missouri, Columbia. Before coming to the U.S., he was an economist at the Center for Economic and Financial Research, an independent economic policy think-tank affiliated with the New Economic School, Moscow, Russia.

Stas has developed a number of Stata modules available in public domain, including software for creation of the bootstrap replicate weights (bsweights), weight calibration (ipfraking), confirmatory factor analysis (confa), simulated annealing (simann), quasi Monte Carlo (scrhalton), and others.

Stas has held a number of leadership roles in the Survey Research Methods Section of the ASA and was the founding chair of its Text Analysis Interest Group (now Section on Text Analysis). He is also a member of several committees of the American Association for Public Opinion Research.