Applied Scientist

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