Ms. Darrow is a senior operations research analyst at CANA Advisors. Ms. Darrow has developed several high impact decision support tools and dashboards that allow end users to model real world scenarios through simulation, optimization, and advanced data analysis. She has also utilized various machine learning and statistical techniques, such as k-means and k-modes classification, text mining, and regression analysis to uncover relationships in data. Ms. Darrow is adept at mathematical representation, distillation of complex problems, and understanding user interaction requirements. She has over three years of experience as an operations research analyst employing predictive and prescriptive analytics techniques. Lucia is an active member of the Military Operations Research Society (MORS), a co-organizer of RLadies Vancouver, and a co-chair of the 2020 Vancouver Datajam. 

As a graduate research assistant in the Manufacturing Systems and Logistics Lab at Oregon State University, Ms. Darrow provided VBA coding, optimization, and simulation support for a two-stage decision support tool which minimized waste in the production of low enriched uranium (LEU) foils. Through her graduate research in the Process Improvement Group at Oregon State, Ms. Darrow applied Lean methodology to a healthcare system to reduce employee burnout and improve organizational resilience. She analyzed the patient treatment process to improve flow and developed an integer programming optimization model for specialized frontline employee scheduling. 

With CANA, Ms. Darrow has contributed to the simulation and optimization of a Marine Prepositioning Force offload through the development of the input and output data miners, which focus on user interaction with the modeling suite. She is currently developing a set of simulation and optimization tools to model a large-scale mining transportation network at different time scales. As lead of CANA's Learning and Development program, she oversees the planning, development, and execution of short courses in a variety of analytics topics.