Christian McGuirk

Analyst

Mr. McGuirk has one year of experience as an analyst and consultant. Since 2019, Mr. McGuirk has worked as an analyst and consultant for Innovative Decisions, Inc., with roles in projects involving discrete event simulations, systems engineering, operations research, data analytics, database management and decision analysis. Mr. McGuirk programmed a graphical user interface to control model parameters for an Excel-based model with an array-based algorithm for estimating the model output of product loaded and unloaded to a port and provide suggestions for the user to address any reneged product. As a support analyst for Marine Corps Installations Command, Mr. McGuirk has automated the data processing workflow to prepare raw data for ingestion into a linear programming optimization model driving annual budgetary decisions.

Prior to Mr. McGuirk’s position at Innovative Decisions, he spent five years working as a process engineer and process control engineer. As a process control engineer, he was responsible for implementing control logic, troubleshooting electrical and mechanical issues, and creating graphical user interfaces that allowed operators to monitor and interact with the process, if needed. As a process engineer, Mr. McGuirk obtained his Lean Six Sigma Green Belt as he spearheaded numerous successful process improvement efforts oriented around quality and production. For example, Mr. McGuirk created the design of experiment plan and used two-way ANOVA to analyze the results of the experiment to determine the optimal run conditions for a high strength grade of product. He spent a year as a researcher at George Mason University in Dr. Erhai Zhao’s Condensed Matter Theory Group, in which he wrote a program in Python that instantiated a 1-D spin chain as a neural network and used unsupervised machine learning and Monte Carlo sampling techniques to determine the ground state energy of the system.

Through his education and experience, Mr. McGuirk has obtained intermediate knowledge in Tableau, Python, SQL, Power BI, Matlab, VBA, and ExtendSim. His analytical techniques include data mining, machine learning algorithms, Bayesian Networks, risk and decision analysis, database development, data visualization, and statistical modeling and simulation

Education

B.S. Chemical Engineering, Virginia Tech, 2011

B.S. Physics, George Mason University, 2019