Carl Ayer provides statistical support to environmental projects across multiple disciplines to guide and defend decisions about environmental management and uses custom data visualizations to promote intuitive interpretation. He ensures that his analyses are transparent, repeatable, and statistically robust. He joined Matrix Solutions Inc while pursuing a bachelor’s degree in Environmental Science with a concentration in Statistics. In addition to a strong background in classical statistics, he extends the concepts of statistical learning and inference to the fringes of his chosen field, including machine learning, Monte Carlo (simulation) methods, exploratory data analysis, and spatial/spatiotemporal analysis. Mr. Ayer likes to work in a programmatic paradigm, creating transparent and repeatable analyses in R and Python. Environmental consulting is Mr. Ayer’s second career, having previously worked as an automotive technician.