Pavel Brusilovskiy, PhD, leads the Predictive Analytics and Data Intelligence practice at Tilman & Company. Dr. Brusilovskiy is a performance-oriented applied scientist who, in addition to teaching and leading multi-disciplinary research teams, has over 20 years of experience of working with Fortune 100 companies. As an expert in statistical modeling, data mining, expert knowledge, and data-driven decision support, he has assisted senior management teams of Cigna, Merck, Conrail, and other leading firms in leveraging predictive analytics in mission-critical initiatives, leading executives and boards of directors to unique insights, effective decisions, growth, and profitability. Projects under his leadership included credit modeling, operational business intelligence, insurance claim duration and cost prediction, customer relationship management, sales force structure optimization, and new product development.
Through thought leadership and practical application spanning decades, Dr. Brusilovskiy has perfected a proprietary approach to identifying the best possible model for a given problem or dataset, which is supported by his extensive of the leading analytical tools, including SAS, IBM SPSS, Eviews, LatentGold, R, and @RISK as well as data mining systems SAS Enterprise Miner, SAS Credit Scoring, Salford Systems Data Miner, JMP, Netica, and IBM SPSS Modeler.
Dr. Brusilovskiy earned a Doctor of Sciences (PhD) in applied statistics & mathematical modeling from the Russian Academy of Sciences as well as M.A. in mathematics and B.A. degrees in engineering from the University of Aviation Engineering. He has published three books and more than 30 articles, covering Financial Risk, Decision Support Systems, Operations Research and Management Science. Further, he has presented at leading conferences on predictive analytics, including the Applied Statistics Symposium in China and the International Conference on Knowledge Discovery and Data Mining in Paris.