Daniel Cannon

Consultant, Data Scientist

Daniel Cannon serves as a consultant to I+E specializing in the areas of machine learning, data architecture design for big data problems, custom data visualization techniques, and full-stack web application development. Daniel is also President of Iterative Consulting, a firm that has worked with Innovate+Educate since 2014. Under Daniel’s leadership, Iterative has expanded into multiple markets across the country and several industries, including healthcare, financial services, human resources, and biomedical research.

Daniel received his MS and BS in Computer Science from the University of New Mexico. As a member of the Complex Adaptive Systems of Systems (CASoS) group at Sandia National Laboratories, Daniel developed agent-based approaches for modeling the spread of infectious diseases, simulating public policy interventions, and providing guidance to US policy makers. Daniel later joined the Translational Informatics Division of the UNM Health Sciences Center where he used machine learning to derive predictive models of neonatal sepsis using protein biomarkers and developed tools to discover novel drug targets by piecing together knowledge mined from academic publications. After leaving UNM, Daniel joined Innovate+Educate’s Employment Tech Division, where he developed novel algorithms and tools for deriving meaningful insights from workforce and labor data.