Applied Scientist (Economics) Intern

Zillow•Seattle, WA

7d•Remote

About The Position

The forecasting and business economics group at Zillow shapes planning and decision-making across Zillow’s businesses. Embedded in the finance organization, the team brings together forecasters, economists, applied scientists, data scientists, and data visualization engineers to transform Zillow’s data and quantitative expertise into insights that inform business decisions. Its work applies forecasting, data science, and causal inference to practical questions from business leaders. This is a nine-week summer internship, running June 14 through August 13. Interns contribute to real business projects, work with Zillow teams, and take part in mentoring, learning, and community experiences. Interns will work on analytical questions with potential revenue impact, using data exploration, modeling, forecasting, causal analysis, experimentation, and communication of findings. The role is categorized as remote. Zillow describes its 2027 internships as based in Seattle, with interns generally working together in person Tuesday through Thursday. Eligible interns will receive a stipend to help offset summer housing and relocation costs.

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 similar tools to prepare data, conduct analysis, and build models.
Ability to express statistical concepts clearly through pseudocode and think through edge cases when designing systems.
Ability to explain analytical findings clearly and collaborate with people from different perspectives and areas of expertise, including nontechnical stakeholders.
Ability to move quickly and ambitiously while maintaining attention to detail, and to adjust between high-level and detailed analysis as context requires.
Thoughtful approach to problem-solving, including checking assumptions, validating results, and distinguishing supported conclusions from uncertainty.
Interest in applying quantitative methods to housing markets, business forecasting, and financial decision-making.
Ability to use AI tools to accelerate and expand work without outsourcing one’s own thinking.

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 how Zillow prices and operates across its 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 to help partners understand and use findings.
Share approaches, results, and recommendations with technical and nontechnical audiences, and document work for a clear handoff.