"Daniel concentrates on using the most advanced technologies to analyze and disseminate large volumes of data using statistically robust methods."

Daniel brings a unique combination of extensive healthcare payer experience, a background analyzing payer and provider claims data, a real world seasoned technical vision, and advanced statistical knowledge. Daniel has been creating complex database systems and conducting sophisticated data analyses since 1997. Over the last 15 years, he has concentrated on researching and delivering analytics on all aspects of healthcare data, ranging from payer claims, provider services and patient history and satisfaction. Daniel concentrates on using the most advanced technologies to analyze and disseminate large volumes of data using statistically robust methods. Combining his technical and statistical expertise, he continues to be on the cutting edge of “big data”, data mining and predictive analytics methodologies. Since 1998, Daniel has worked with Howard Pierce on healthcare provider cost containment claim analytics, detecting in excess of $700 mm in overpayments. A published author in public policy and current professor at California State University Channel Islands, he holds his Ph.D. from Cornell University and a Bachelors of Science with Honors in Engineering and Applied Sciences from the California Institute of Technology.