Clayton Mcgee Email & Phone Number

Denver, Colorado, United States

Leader within the FSRRC (Financial Services Risk, Regulatory and Compliance) practice focused on delivering quantitative analytics-driven risk management solutions to large financial service clients. Serves as one of the technical leaders within the practice and often utilizes AI, ML, and statistical methods to serve clients. Manages the development and day-to-day implementation of the solution approaches at multiple clients at a time, and leads proposal responses and interaction with client stakeholders during the sales process.

Denver, Colorado, United States

Develop and deliver specific business solutions to clients by utilizing machine learning and statistical methods. Responsibilities focus on end-to-end development and implementation of data science solutions, including optimal solution design in collaboration with client stakeholders, data gathering and model development via extensive Python and SAS programming, and working with both internal and client teams to validate, document, visualize, disseminate, and implement the solution.Specific methods of deep exposure include time series modeling, natural language processing, logistic regression, multiple regression, principal component analysis and cluster analysis. He is proficient in Python, R, SAS, MATLAB, SQL, Excel and Tableau.

Fort Collins, Co

Lead author on a publication in a leading peer-reviewed scientific journal. Performed requisite research through advanced programming and data visualization analyses during full-time research employment concurrent with completion of Master's Degree and Thesis. Presented research results to leading professionals at multiple scientific conferences.

Raleigh, Nc

Detailed analysis and programming routines built in MATLAB to understand rain-drop size distributions. Compiled results into succinct findings useful to the National Weather Service for understanding high impact rain events.

Binghamton, Ny

Helped office meteorologists better predict poor visibility due to fog at airports across New York and Pennsylvania by appropriately tuning the coefficients in a simple linear additive model based on available atmospheric parameters. Improved the forecasters’ understanding of lake effect snow events by categorizing similar events.

Master Of Science (M.S.), Analytics

Master Of Science (M.S.), Atmospheric Science

Bachelor Of Science (B.S.), Meteorology, Valedictorian