A company is looking for an Applied Scientist to develop and refine forecasting models for the housing market.
Key Responsibilities
Develop and refine forecasting models for national, regional, and local housing markets
Collaborate with applied scientists, data scientists, economists, and engineers to derive actionable insights from large-scale data
Utilize AI tools and emerging technologies to enhance research productivity and forecasting workflows
Required Qualifications
Master's or PhD degree in a quantitative field such as Mathematics, Statistics, or Economics, or equivalent practical experience
2+ years of experience with time series and / or spatial forecasting problems
Solid foundation in econometric methods and modern machine learning techniques relevant to forecasting
Hands-on experience with large-scale time series or panel datasets, including data cleaning and preprocessing
Proficiency in software development best practices and tools, including version control systems like Git
Applied Scientist • Pasadena, Texas, United States