SEATTLE—August 28, 2012—Context Relevant (www.contextrelevant.com), a leading provider of Big Data modeling and analytics software, announced today key additions to its data science team to accelerate its mission to empower enterprises to profit from their Big Data. The company added Dustin Hillard, Ph.D. as its Director of Engineering and Scott Golder as a Data Scientist and Staff Sociologist.
Hillard, who received his Ph.D. in Electrical Engineering from the University of Washington, is a recognized data science and machine learning expert who has published more than 30 papers in these areas. Previously at Microsoft and Yahoo!, he spent the last decade building systems that significantly improve large-scale processing and machine-learning for advertising, natural language and speech.
Golder has conducted research in both academia and industry and is a leading computational sociologist. He has held research positions for leading organizations, including the Social Computing Lab at HP Labs, Microsoft and Google, and is currently on leave from the Cornell University Sociology Ph.D. Program. Golder, who received a master’s degree from the MIT Media Laboratory and a B.A. in Linguistics from Harvard University, brings a deep passion for helping customers use their Big Data to better connect with and serve their audiences.
“Dustin and Scott are recognized experts in the fields of machine learning and computational social science and I am thrilled to announce they’ve joined our team,” said Stephen Purpura, Context Relevant CEO and Co-Founder. “Today Big Data analytics is unbelievably complex and is so expensive that few companies have profited from it. Context Relevant is changing that by building the expertise of our data science team into our software.”
Context Relevant provides on-premises and cloud-based applications that turn enterprise information workers into Big Data scientists. Context Relevant’s Flexible Analytics and Statistics Technology™ (FAST) system unlocks the potential of Big Data by empowering enterprise analysts with capabilities that—until now—required a large, highly skilled and expensive team of data scientists. By making it easy to weave together large and disparate data sources, Context Relevant enables its customers to ask questions and get answers in seconds that previously required days or even weeks.
“I’ve thought about the opportunity to generalize and improve enterprise Big Data science for more than a decade,” said Hillard. “By enabling enterprises to build, continually improve and execute their analytical models, we are changing the game and making it easier for companies to profit from their Big Data.”
Golder, who is a frequent news commentator and whose work has been published in leading journals, including Science, ACM and IEEE, is looking forward to enabling the benefits businesses can derive by bringing these capabilities in-house. “Big Data analytics combined with social science offers companies the incredible opportunity to better understand and predict the behavior and preferences of their customers to better serve them,” said Golder. “To do something like this today requires employing someone like me, whereas at Context Relevant we are building these smarts into our software.”
About Context Relevant:
Context Relevant is a leading provider of Big Data analytics modeling and analytics software. Whether a company is struggling to find and hire data scientists or wants to make its existing team more efficient, Context Relevant reduces risk, simplifies data handling and adds the capability to systematically turn an organization’s Big Data into a competitive advantage. For more information please follow @contextrelevant, call +1-800-980-DATA, or visit: contextrelevant.com.
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