Summary
Samuel Croker is a Senior Solutions Architect at SAS with 20+ years of experience translating statistical and machine learning methods into production-ready, auditable pipelines across cloud, cluster, and containerized environments. He blends hands-on coding in Python and R with presales and customer-facing architecture, specializing in SAS Viya integrations that enable polyglot teams and high-performance analytics workflows. A mathematically grounded problem-solver with an MS in Statistics, he focuses on practical choices—statistical inference or stochastic predictors—matched to business needs rather than tool fashion. His background ranges from mainframe DB2 administration to enterprise predictive modeling in health and life sciences, and he enjoys teaching as much as building, often experimenting with distributed computing and AWS deployments. Not obvious from the title: he’s spent three decades coding math and statistics and prioritizes repeatability, auditability, and extendability across the full analytics life cycle.
10 years of coding experience
10 years of employment as a software developer
BS, Mathematics, BS, Mathematics at University of South Carolina-Columbia
MS, Statistics, MS, Statistics at University of South Carolina