John Charles

Mr. Charles is an exacting data scientist, content to work with data of all kinds. He is the company’s go-to person for complex statistical questions and assignments that require advanced analytical techniques.

John has extensive knowledge and experience performing parametric and non-parametric statistical analysis, statistical modeling, predictive analytics, and big data analysis. He is skilled in the use of state-of-the-art data management and statistical analysis software including SPSS, R, and SAS, among others.

While he supports a wide variety of projects with simple analysis and report preparation, John stands out for his specialized work. For the Maine Shared Needs Health Assessment and Planning Process (SHNAPP) he analyzed and reported on 161 health indicators at the state, county, and urban levels. For the City of Buffalo (NY) Youth Risk Behavior Survey, John’s analyses showed a statistically significant link between academic performance and student health. For Unum, a disability insurer, he used predictive modeling to identify drivers of consumer satisfaction. Using data from the Virginia Youth Risk Behavior Survey, he segmented youth by peer crowds and identified two groups with higher rates of risky behaviors. To demonstrate the effects of implicit bias in the evaluation of judges in Massachusetts, John used regressions and identified specific demographic groups most susceptible to implicit bias.