Job Title
Head of ForecastingJob Description Summary
Key Objectives:Job Description
Develop & Maintain Best-in-Class CRE Forecasting Infrastructure (50%)
· Oversee new architecture that houses end-to-end solution for Americas CRE forecasting, using best-in-class practices around macro-to-micro techniques and reconciliation.
· Ensure diagnostics and quality controls are consistent with best-in-class infrastructure practices.
· Elevate modeling capability to include traditional econometric techniques for forecasting (e.g., ARIMA, VAR, [G]ARCH, VECM), with traditional panel data techniques, ML models (recurring neural networks, Prophet) and evolving AI models, emphasizing accuracy (out-of-sample, back-testing) and credibility (theoretical foundations).
· Ensure platform capabilities meet basic competitive needs.
· Partner with relevant internal or external stakeholders to integrate AI/ML-driven solutions.
· Develop and oversee best-in-class maintenance procedures for models.
· Manage forecast production.
· Automate any and all data transfers, manipulation and other production-related processes where possible to maximize efficiency in conjunction with PRI (Property Research & Intelligence), TDS (Technology & Data Solutions) and other QIG teams.
· Produce methodological white papers and infrastructure documentation consistent with best-in-class practices.
· Partner with other QIG leadership to integrate forecasting outputs into critical internal and external analytical tools and products.
Expand & Develop Derivative Forecast-Adjacent Analytical Products (30%)
· Partner with Head of Data Science & Geospatial Analytics develop derivative outputs from forward-looking forecast outputs, using appropriate, scalable techniques.
· Partner with Head of Commercial Analytics to integrate products into tools and products.
· Identify opportunities to develop leading indicators, other differentiated analytical products/capabilities and advise on key resources needed for capacity building.
Augment Cushman & Wakefield Analytical Brand Value (10%)
· Expert on economic, financial market and other matters related to modeling CRE markets.
· Partner with Think Tank and Americas Research (as appropriate) on thought leadership that promotes brand value, House View and differentiation.
· Brand ambassador at select industry events and with the media.
· Serve as a client-facing resource on matters related to the Americas outlook, both at a micro and macro level, but often with an emphasis on the micro thematics.
· Point of contact for all subnational forecast-related matters.
· Responsible for working with global counterparts to coordinate thought leadership content and to elevate the profile of QIG research at all levels.
Management & Talent Development (10%)
· Lead team of forecasters and consultants.
· Continuous develop and augment skillsets as technology and AI capabilities evolve.
· Oversee complex, multi-stakeholder workstreams, ensuring technical excellence and strategic alignment across projects.
Requirements:
· Ph.D or Master’s degree in Economics, Applied Economics, Statistics, Finance, Real Estate, or in a related field preferred.
· 7-10 years of experience in time-series analysis and forecasting, preferably in a real estate setting. Experience in a tech setting also preferred.
· Experience with architecting and engineering econometric/forecasting modeling infrastructure.
· Expertise in various econometric modeling techniques, time series analysis, panel data, and machine learning. Experience with AI (nontraditional ML) a plus.
· Strong proficiency in one or more programming languages (Python preferred). Proficiency with cloud systems (e.g., Azure, AWS) a plus.
· Ability to work effectively at all levels of the organization in pursuit of business development.
· Excellent documentation, communication, and stakeholder management skills; comfortable operating as the technical translator between analytical domain experts and other stakeholders (data engineers, business leadership, clients).
· Excellent documentation and communication skills for technical audiences. Ability to lead or participate meaningfully in technical discussions.
· Exposure to geospatial data concepts, CRE and socioeconomic/demographic datasets.
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