Applied Scientist
virtual vocationsDenver (CO)
About the role
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
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
More like this