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SiteWit CEO and executives

Executive Summary. Based on our data team's research, Ricardo Lasa is the SiteWit's CEO. SiteWit has 30 employees, of which 5 are in a leadership position.
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Name & TitleBio
Ricardo Lasa

CEO

Ricardo Lasa's LinkedIn

​Don Berndt Ph.d

Founder

​Don Berndt Ph.d's LinkedIn

Don is a professor in the College of Business at the University of South Florida. His research interests are centered on business intelligence technologies such as data warehousing, data mining, and text mining. A particular emphasis of his work is the application of these technologies in healthcare, including data and text mining for electronic medical records. More recent work has focused on information markets as another mechanism for prediction and collective intelligence (working together with Ricardo on Agorx). He has published more than 75 research papers on these topics and worked with a number of entrepreneurial technology firms, as well as other organizations throughout his career. His first exposure to entrepreneurism was a position as a LISP programmer at Cognitive Systems, an artificial intelligence start-up associated with Yale University. That was followed by work in scientific computing and healthcare analytics at other companies. Working with Ricardo on SiteWit has provided an opportunity to apply data warehousing and data mining technologies to website traffic analysis and the development of learning algorithms for managing paid search. Don received his Ph.D. in Management Information Systems from the Stern School of Business at New York University and M.S. in Computer Science from Stony Brook University.

Christopher Lord

COO

Christopher Lord's LinkedIn

Chris Lord is a CTO at SiteWit and COO at SiteWit and is based in Lutz, Florida. He has worked as Ecommerce Developer at Rivergy Inc and Senior Ecommerce Developer at Web Piston.

James McCart Ph.d

Chief Innovation Officer

Jesse Baynard

Chief Engineering Officer

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SiteWit founders

Name & TitleBio
Ricardo Lasa

CEO

Ricardo Lasa's LinkedIn

​Don Berndt Ph.d

Founder

​Don Berndt Ph.d's LinkedIn

Don is a professor in the College of Business at the University of South Florida. His research interests are centered on business intelligence technologies such as data warehousing, data mining, and text mining. A particular emphasis of his work is the application of these technologies in healthcare, including data and text mining for electronic medical records. More recent work has focused on information markets as another mechanism for prediction and collective intelligence (working together with Ricardo on Agorx). He has published more than 75 research papers on these topics and worked with a number of entrepreneurial technology firms, as well as other organizations throughout his career. His first exposure to entrepreneurism was a position as a LISP programmer at Cognitive Systems, an artificial intelligence start-up associated with Yale University. That was followed by work in scientific computing and healthcare analytics at other companies. Working with Ricardo on SiteWit has provided an opportunity to apply data warehousing and data mining technologies to website traffic analysis and the development of learning algorithms for managing paid search. Don received his Ph.D. in Management Information Systems from the Stern School of Business at New York University and M.S. in Computer Science from Stony Brook University.

SiteWit executives FAQs

Zippia gives an in-depth look into the details of SiteWit, including salaries, political affiliations, employee data, and more, in order to inform job seekers about SiteWit. The employee data is based on information from people who have self-reported their past or current employments at SiteWit. The data on this page is also based on data sources collected from public and open data sources on the Internet and other locations, as well as proprietary data we licensed from other companies. Sources of data may include, but are not limited to, the BLS, company filings, estimates based on those filings, H1B filings, and other public and private datasets. While we have made attempts to ensure that the information displayed are correct, Zippia is not responsible for any errors or omissions or for the results obtained from the use of this information. None of the information on this page has been provided or approved by SiteWit. The data presented on this page does not represent the view of SiteWit and its employees or that of Zippia.

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