Applied Scientist
Core
Develop hierarchical forecasts for the housing market at various regional levels using traditional econometrics and machine learning to predict trends 1-2 years in the future.
Role type
Applied Scientist (Time Series & Hierarchical Forecasting)
Builds
Monthly housing market forecasts, scenario models for stress-testing, and production ML models.
Domain
Real Estate / Housing Market Analytics
Deliverable
production ML models
Required skills
Traditional econometric methods, Machine learning, Time series forecasting, Hierarchical forecasting, Feature engineering, Distributed computing (Spark), Model evaluation and validation, Cloud-based ML deployment, AI agent development
Preferred skills
Strong interest in housing market dynamics, Independent research capabilities
Technologies
Spark, Cloud platforms
Responsibilities
Extract economic and demographic features to predict housing market trends, Collaborate with engineering to deploy models into production, Contribute to monthly forecast production and communicate outlook to leadership, Develop scenario models for company-wide stress-testing
Seniority
Mid-level (2+ years experience)
