Josh Hoodin is the manager of statistics and predictive modeling for Retail Occupier Services (ROS), a specialty practice within Newmark.
Mr. Hoodin has over 14 years of experience creating location-based forecasting models in the commercial real estate industry. He worked for Newmark as a statistical consultant for four years before being brought on board. Before joining the team at Newmark, he worked at JLL as a Senior Associate. There, he was the sole statistical analyst for the retail department, creating models of store performance, analog forecasts, and performing ad hoc studies. Mr. Hoodin got his start in site selection and retail modeling at the consulting firm Pitney Bowes Business Insight (previously Thompson Associates).
Mr. Hoodin has gained cross-industry experience in retail, restaurants, finance, telecommunications, and transportation. Josh has developed models for more than 40 clients, ranging from large household names with thousands of locations, to small local players with only a handful. He has expertise in advanced statistical methods and the most current machine learning techniques including multivariate regression, tree-based models, ensemble learning, cluster analysis, resampling methods, vector autoregression, neural networks, and hierarchical modeling.
- Eastern Michigan University: Master of Arts, Econometrics, 2006.
- Eastern Michigan University: Bachelor Business Administration, 2003.