Episode 10: Rich Hughes, Head of Data Science, RealPage
Go in depth on how Artificial Intelligence is shaping the multifamily industry and what future technology advancements will further enhance operations and resident experiences.
Rich Hughes discusses the role of length, depth and breadth of data in powering truly meaningful AI output, and what it takes to build a successful, high-functioning AI team.
Arben Skivjani
Deputy Chief Economist and Director of Forecasting
RealPage, Inc.
Arben Skivjani serves as a Deputy Chief Economist and Data Scientist for RealPage, Inc. His primary focus is on forecasting and econometric modeling, economic impact studies, reporting and analysis of macroeconomic trends that affect the multifamily industry. Prior to joining RealPage, Arben worked for several government and private sector entities, including the District of Columbia Department of Employment Services, Center for Business and Economic Development at the University of Alabama and Camoin Associates in Upstate New York.
Arben is heavily involved in the Dallas/Fort Worth Association for Business Economics where he currently serves as Vice President and is a member the National Association for Business Economics.
Arben holds a master’s degree in economics from The University of Alabama.
Rich Hughes
Senior Vice President, Data Science
RealPage, Inc.
Rich Hughes first entered the data revolution with apartment owner/operators AMLI and Archstone for over a decade, and is now head data scientist with RealPage. Hughes believes that today’s winners in complex, asset-intensive, service-based industries—from Amazon to apartments—have discovered the operational trifecta: over-delivering on promises while keeping the operation streamlined and affordable. He spends his days creating centralized command and control capacity for apartment operators, mainly regional managers, to streamline their operations through better and faster decision-making. He does this by analyzing data to predict outcomes, giving apartment operators prescriptive recommendations that are mathematically solvent and intelligence that is continually learning.