Riley is a data scientist with a strong background in mathematics, statistics, and business intelligence who is passionate about helping organizations leverage data and analytics to solve problems and make better decisions. In past roles, he has worked on a variety of projects that range from supporting scientific research to leading a business analytics team. Along the way, Riley has used a variety of techniques to extract value and insight from data including visualization, reporting and dashboards, machine learning and predictive modeling, Internet of Things, and statistical analysis. Recently, Riley worked with a digital billboard company to stream data from their billboards to a cloud storage system where he used machine learning algorithms to train models to predict future billboard failures, enabling proactive maintenance. In any case, Riley strives to find simple and effective solutions that not only provide value, but are easy to understand and implement.
Uncertainty that comes from knowledge (knowing what you don’t know) is different from ignorance – Isaac Asimov