Senior Applied Scientist, Forecasting

Zillow

1d • $152,900 - $257,100 • Remote

About The Position

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. 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 exceptions.

Requirements

• 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 discipline), or equivalent practical experience.
• Proficient in Python and SQL for building, evaluating, and deploying models.
• Demonstrated experience monitoring, debugging, and maintaining models in production environments.
• Experience explaining complex models and analytical concepts to stakeholders with varied technical backgrounds, using clear takeaways, succinct insights, and effective visualizations.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level