Sears Holding Corp.’s David Davtian Joins Earnix North America
Expert in pricing science to support Earnix’s continued growth
Westport, CT – June 25, 2014 – Earnix, a leading provider of integrated pricing and customer analytics solutions for banking and insurance, today announced the addition of pricing and analytics expert David Davtian as one of the company’s Senior Professional Services Consultants. David will further the breadth and depth of the Earnix team in the North America region, leading the on-the-ground delivery of advanced analytics projects for customers in the United States and Canada.
With over 15 years of pricing experience in a variety of industries including retail, CPG and financial services, David brings to Earnix exceptional analytics and modelling skills, as well as an expertise in delivering superior pricing solutions to clients. Before joining Earnix, David served as the Divisional Vice President of Pricing at Sears Holding Corp., where he was responsible for managing the apparel pricing team and developing and implementing predictive modelsand optimization tools. Prior to Sears, David was Senior Director of Science and Analytics for Model N, a revenue management solutions company for Life Sciences and Technology industries. He also formerly served as the Director of Research and Analytics, as well as the Director for Services, at Nomis Solutions, and Director of Econometric Modeling at DemandTec (an IBM company). David holds an MBA from the American University of Armenia, an MS in statistics from University of Maryland, and an MS in Physics from Yerevan State University.
“We are pleased to welcome David Davtian to our North American team,” said Reuven Shnaps, Ph.D., Vice President of Professional Services for Earnix. “He’s a skilled modeler and pricing expert with an impressive, versatile background that we’re sure will bring significant value to our customers in the banking and insurance industries.”
Earnix provides an advanced analytics platform designed for the financial services industry, which integrates real-time decision-making capabilities into the business process, delivering significant results.
Earnix’s modeling, algorithms, and Machine Learning capabilities automate the rapid deployment of customer-centric offers by considering variables such as price, product features, and distribution channels, to optimize KPIs such as revenue, profit, sales volume, and customer satisfaction.
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