The team at Enplus Advisors Inc. comes from diverse backgrounds including computer science, psychology, and quantitative finance. They have developed predictive analytics solutions for companies in verticals such as IoT, healthcare, finance, marketing, and technology.
Daniel Gerlanc has worked as a data scientist for over 10 years. He spent 5 years as a quantitative analyst with two Boston hedge funds before starting Enplus Advisors Inc, a predictive analytics consultancy, in 2011. At Enplus, he works with clients in different industries to improve existing analytic processes and develop new ones. He has coauthored several open source R packages, published in peer-reviewed journals, and is active in local predictive analytics groups. He is a graduate of Williams College.
Phil Enock has over 8 years of analytics experience spanning industry and academia. In 2015, he completed his PhD in Experimental Psychological Science at Harvard where, as part of his research, he directed a quantitative research program of web-based and mobile app experiments that ultimately collected over 3 million responses. Prior to joining Enplus at the start of 2017, he worked as a data scientist at Wayfair, applying machine learning to e-commerce pricing and cost modeling, and at the Democratic National Committee on probabilistic machine learning models and big data pipeline development. He holds a B.A in Computer Science from Williams College and has enjoyed writing code since age 12.