Applied Scientist

Zillow

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Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $139,400–$222,600 / yr
Employment: Full-time
Posted: 20 days ago
Freshness: Confirmed live today
Closes: Dec 7, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $202k

This role $181k

$125k $271k

below market most similar roles pay here above market

This role pays less than 60% of similar roles. Most pay $162,000–$241,906 — the blue band above. At the midpoint, this role pays about $181k versus about $202k for comparable roles.

Based on 240 similar postings.

Employer

About Zillow

Zillow Group is a leading real estate and rental marketplace providing consumers with data, tools, and services to find, buy, sell, rent, and finance homes, and connecting buyers with agents and lenders. Industry: Real Estate Technology & Marketplace

Zillow currently has 49 open roles on FindRole.

Listed pay typically runs $164,400–$262,600 across 40 roles with salary data.

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At a glance

TL;DR · Applied Scientist

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The Applied Scientist joins a dynamic team to analyze and predict housing market trends using a database of over 100 million homes and transactions. This role focuses on traditional econometrics and machine learning, specifically addressing time series and hierarchical forecasting problems. Key responsibilities include collaborating with data scientists and economists to develop regional forecasts, extracting economic and demographic features to predict trends one to two years out, and deploying models into production environments. The scientist will also perform scenario modeling for stress-testing and contribute to monthly forecast production. Required technical skills include proficiency in data cleaning, preprocessing, and feature engineering for time series data, experience with Spark for distributed computing, and knowledge of cloud-based platforms for monitoring models. Candidates must possess a Master’s or PhD in a quantitative scientific field.

What does a Applied Scientist earn?

Median $208800 from 61 postings across 10 companies.

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Skills

Econometrics Machine Learning Time Series Forecasting Hierarchical Forecasting Spark Distributed Computing Feature Engineering Model Deployment Cross-Validation Backtesting

What you'll do

Develop hierarchical forecasts for the housing market at various regional levels.
Identify economic and demographic driving forces to extract features for predicting market trends.
Collaborate with the engineering team to deploy machine learning models into production environments.
Contribute to monthly forecast production and communicate performance metrics to senior leadership.
Develop scenario models to capture diverse housing market outcomes and stress-testing frameworks.
Perform data cleaning, preprocessing, and feature engineering for large-scale time series datasets.
Design and implement robust model evaluation strategies including cross-validation and backtesting.
Build AI agents to automate manual work processes.

What we're looking for

Master’s or PhD degree in Mathematics, Statistics, Economics, Econometrics, Physics, Earth Sciences, or a related scientific field.
2+ years of proven experience working in the time series or spatial forecasting space.
Strong foundation in traditional econometric methods and modern machine learning techniques.
Proficient in data cleaning, preprocessing, and feature engineering for time series data.
Experience with large-scale datasets and familiarity with distributed computing frameworks such as Spark.
Ability to design and implement robust model evaluation and validation strategies, including cross-validation and backtesting.
Proficient in cloud-based platforms and tools for deploying and monitoring machine learning models.
Proficient in building AI agents to automate manual work.