Applied Scientist

Job Summary

Working remotely in a full-time capacity, the Applied Scientist will develop hierarchical forecasts for the housing market utilizing econometric methods and machine learning, while collaborating with cross-functional teams to deploy models and communicate insights to stakeholders.

Key responsibilities

• Collaborate with applied scientists, data scientists, and economists to create hierarchical forecasts for various regional housing markets
• Identify economic and demographic factors influencing housing market trends and extract relevant features for predictive modeling
• Contribute to monthly forecast production and develop scenario models for stress-testing frameworks

Required qualifications

• Master's or PhD degree in Mathematics, Statistics, Economics, Econometrics, Physics, Earth Sciences, or a related scientific field
• 2+ years of experience in time series or spatial forecasting
• Strong foundation in traditional econometric methods and modern machine learning techniques
• Proficiency in data cleaning, preprocessing, and feature engineering for time series data
• Experience with cloud-based platforms for deploying and monitoring machine learning models