With more than 30 years of institutional investment experience and a long history of designing and developing sophisticated database and machine learning tools, Peter has focused most of his career on the intersection of these two separate, but wholly complementary skill sets: investment research and data science. Peter has focused much of his time and energy on the burgeoning field of machine learning, including data visualization and dashboards, data analysis and developing learning tools that help take advantage of the enormous amounts of data and information which can be harnessed today. ​

Peter is a highly experienced researcher with over two decades with leading consulting firms NEPC and Segal Marco Advisors (nee Rogerscasey) and developed a deep knowledge of the financial markets and the community of leading investment managers. Peter has built his career on a strong academic background, with designations from the CFA Institute, the Chartered Alternative Investment Analyst Association, the Financial Data Professionals Association, and the Sustainability Accounting Standards Board.