United States onlyAbout 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.
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 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.
Here at Zillow, we value the experience and perspective of candidates with non‑traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences.
Get to know us
At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company that's reshaping an industry and helping more people make home a reality.
Zillow is honored to be recognized among the best workplaces in the country. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025, and included on the PEOPLE Companies That Care® 2025list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.
No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.
Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
