Applied Scientist (Economics) Intern

Zillow•Seattle, WA

8d•$104,000 - $166,000•Remote

About The Position

The forecasting and business economics group is embedded in Zillow’s finance organization and conducts research to inform planning and decision-making across Zillow’s businesses. The group brings together forecasters, economists, applied scientists, data scientists, and data visualization engineers to turn Zillow’s data into actionable insights using quantitative methods in forecasting, data science, and causal inference. This is a nine-week summer internship running June 14 through August 13, 2027. Interns work on projects that contribute to the business, gain hands-on experience, and connect with mentors, leaders, and their intern cohort. The internship is categorized as remote; remote employees work from a physical location of their choice that must be identified to the company. Zillow states that its 2027 internships are based in Seattle and follow a hybrid schedule, with interns generally working together in person Tuesday through Thursday. Eligible interns will receive a stipend to help offset summer housing and relocation costs. The intern will apply quantitative methods to business questions, housing and economic data, forecasting, causal analysis, and experimentation. The work includes developing analytical approaches and models, evaluating results and uncertainty, producing reproducible analyses and visualizations, and communicating findings to technical and nontechnical audiences.

Requirements

Currently pursuing a master’s or PhD in statistics, economics, data science, applied mathematics, quantitative finance, or a related quantitative field.
Expected graduation between December 2027 and Summer 2028.
Strong foundation in probability, statistics, and regression analysis, with exposure to econometrics.
Coursework or research experience in time-series and causal analysis.
Ability to use Python or a similar tool to prepare data, conduct analysis, and build models; ability to express statistical concepts through pseudocode and consider edge cases when designing systems.
Ability to explain analytical findings clearly and collaborate with nontechnical stakeholders and people with different perspectives and expertise.
Analytical and detail-oriented, with the ability to create structure from ambiguity and learn in a fast-paced environment.
Ability to work with large amounts of data and move quickly without sacrificing attention to detail.
Thoughtful approach to problem-solving, including checking assumptions, validating results, and distinguishing what data supports from what remains uncertain.
Ability to use AI tools to accelerate and expand work without outsourcing independent thinking.
Interest in applying quantitative methods to housing markets, business forecasting, and financial decision-making.

Responsibilities

Partner with a manager and stakeholders to translate open-ended business questions into analytical approaches and clear deliverables that can produce tangible revenue benefits.
Explore, clean, and validate housing, economic, business, or financial data; document assumptions and identify data-quality issues.
Build and compare models to support prediction and forecasting.
Transform observational data into causal models using appropriate identification strategies.
Design experiments to improve pricing and operations across Zillow’s businesses.
Evaluate models using appropriate baselines and time-based validation, and communicate uncertainty, limitations, and trade-offs.
Investigate trends, forecast errors, and drivers of business performance to develop actionable insights.
Create reproducible analyses, visualizations, or reporting workflows that help partners understand and use findings.
Present approaches, results, and recommendations to technical and nontechnical audiences, and document work for a clear handoff.