Leading team focused on AI and data science for real estate investment strategy.

Led newly-formed department to spearhead portfolio strategy, leveraging machine learning and advanced predictive analytics to identify attractive investment opportunities, and alternative data to quantify the impact of emerging catalysts on investment strategy.

Led full-stack Data & Analytics organization that architected the company's integrated cloud Data Platform, enabling faster time-to-insight and analytics-driven collaboration across business units. Data Science group operated at center of a hub-and-spoke analytics organization, concentrating on strategic decision-making and tactical opportunities to drive revenues and operating margins.

Designed and managed an industry-leading data science & research team, spearheading cross-functional initiatives to deliver insights that merged domain expertise with interpretable ML, spatial analytics, time series forecasting, and causal modeling.

Co-Head of research team at global investment bank; produced differentiated analytics that leveraged ML techniques (R/Python) for forecasting real estate markets, natural language processing (NLP), and real asset valuation.

Co-Head of research team at boutique investment bank. Developed advanced analytics models in R & Python for time-series forecasting, natural language processing (NLP), and asset valuation.

Head of U.S. real estate research team, encompassing all major property sectors. Led global and cross-departmental collaboration of property sector analytics, providing differentiated insight to Morgan Stanley's institutional and wealth management clients.

Head of Research team covering all major property sectors. Developed analytical models to forecast commercial real estate prices, and estimate valuations of domestic and global real estate portfolios. Wall Street Journal #1 Real Estate Sector Analyst, 2005.