Econometric Forecasting Lead

What you'll do

• Monitor and track forecast accuracy using metrics like RMSE and MAE to provide regular back-testing reports.
• Serve data to the analytics team for the development of actionable forecast accuracy dashboards.
• Refine existing variables and coefficients while exploring new economic inputs to improve model precision.
• Conduct quantitative research to evaluate and improve commercial real estate models, data series, and estimations.
• Lead the quarterly review process for forecast accuracy by incorporating analyst feedback and external factors.
• Develop and innovate new forecast models for specialty real estate sectors, nowcasts, and space-level analytics.
• Maintain clear documentation regarding forecast methodologies, inputs, and variables.
• Communicate forecast processes, results, and model validations to external customers.

What we're looking for

• Master's degree in econometrics, statistics, data science, or a related field from an accredited, not-for-profit, in-person college or university.
• Advanced degree (Master’s, PhD) in econometrics, statistics, data science, or a related field from an accredited, not-for-profit, in-person college or university (preferred).
• 5-7+ years of relevant experience in econometric modeling, quantitative analytics, or commercial real estate forecasting.
• Strong proficiency in SQL (SSMS/Databricks), R, and Python for data manipulation, analysis, and modeling.
• Expertise in econometric models, including regression analysis, time series forecasting, and advanced statistical techniques.
• Proven experience in developing and refining forecasting models using large data sets.
• Strong understanding of commercial real estate dynamics, market drivers, and forecasting challenges.
• Experience with Python-based data science tools, cloud platforms, and space-level analytics (preferred).