Vlad Skorokhod is a data scientist, system engineer and experimental physicist with a combined 20+ years of experience in solving complex business and technical problems with predictive modeling and building data acquisition and measurement systems. He has a PhD in engineering from Queen’s University (Kingston, Canada), a doctorate in experimental physics and BSc in electrical engineering. He is a co-inventor of 51 US patents, a certified Six Sigma Black Belt and a Johns Hopkins University certified data scientist.
Vlad has worked in corporate and academic environments as a principal scientist, multidisciplinary project team leader and competency manager. He spent a bulk of his career at Xerox research labs building test and measurement platforms to support the development of advanced laser printing technology. Long before data science became ubiquitous, he was developing predictive models to extract technical insights from raw experimental data and convert them into decisions and recommendations to set the directions for further technology development. Later on, as a data scientist in residence, Vlad developed a predictive maintenance algorithm for the technical support team to predict customer calls from machine log data. He also worked with the corporate sales team and developed a predictive model for sales process troubleshooting.
In his present role as a principal consultant, Vlad has been helping corporate clients discover risks, threats and opportunities and address them with instant actions. His past clients include technology startups, high-profile business architecture consultants, and global technology companies such as Microsoft and Fujifilm. Vlad specializes in building scalable predictive models for customer browsing behavior, cross-device identify matching, event sequences and predictive maintenance.