Senior Applied Scientist, Forecasting

## About the team

The forecasting group at Zillow provides critical visibility through macroeconomic and housing market uncertainty, shaping planning across Zillow’s businesses. We bring together forecasters, economists, applied scientists, data scientists, and data visualization engineers to build and maintain the forecasts that guide decision‑making. Working with proprietary, industry‑leading data and rigorous forecasting methods, we translate housing market signals into actionable business outlooks. In close partnership with finance, product, and other business teams, we are modernizing how forecasts are produced, evaluated, and operationalized to create a more automated, scalable, and decision‑focused forecasting function.##

About the role Zillow is seeking a Senior Applied Scientist to join our forecasting organization. In this role, you will design, test, and deploy advanced forecasting models that shape strategic and operational decisions across Zillow. You will work at the intersection of data, economics, and business context to develop and continuously improve forecasts that matter for our customers and our business.

You will regularly translate forecast results into clear insights for senior leaders, clarifying current performance, expected trajectories, key drivers, and the uncertainty and trade‑offs that shape our plans.##
** You Will Get To:
*** Analyze large, complex datasets to understand buyer and seller behavior and uncover the drivers of key real estate and business outcomes.
* Develop and deploy time‑series and econometric forecasting models that address critical customer, housing market, and business questions, without exposing proprietary product details.
* Own the end‑to‑end modeling lifecycle, including scoping, feature engineering, model development, experimentation, deployment, monitoring, and model explainability.
* Translate forecasts into clear insights and recommendations for senior leadership, helping stakeholders understand drivers, uncertainty, and trade‑offs that guide Zillow’s strategy.
* Partner cross‑functionally with finance, product, engineering, marketing, and operations to scale and improve forecasting capabilities across Zillow.
* Improve and contribute to shared forecasting tools, data pipelines, and processes used across the company.
* Collaborate with other applied scientists and data scientists to develop novel solutions to real estate and business problems.

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited  California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $ - $ annually.

This base pay range is specific to these locations and may not be applicable to other  Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range for this role is $ - $ annually. The base pay range is specific to these locations and may not be applicable to other  addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location.

Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.## Who you are
* Strong experience with quantitative time‑series forecasting techniques and a practical understanding of trade‑offs between performance, explainability, and scalability.
* Approximately 7+ years of applied data science experience, including substantial hands‑on work in forecasting, predictive modeling, or econometric analysis (industry or equivalent research experience).
* Advanced degree (MS or PhD) in a quantitative field (e.g., Economics, Operations Research, Data Analytics, Statistics, Computer Science, Mathematics, Information Management, Engineering, or related quantitative…