Applied Scientist (Economics) Intern

About The Team

The forecasting and business economics group at Zillow shapes planning and drives decision making across Zillow’s businesses. Embedded in the finance organization, this team prioritizes research projects that directly impact the company’s bottom line and growth.

About The Role

• 9-week summer internship program, running June 14th through August 13th.
• Opportunities to bring ideas and perspectives to real projects alongside Zillow teams.
• Build hands-on experience, connect with mentors and leaders, and participate in learning and community experiences.
• 2027 internships are based in Seattle and follow a hybrid schedule (in-person Tuesday-Thursday).
• Eligible interns will receive a stipend to help offset summer housing and relocation costs.
• This role has been categorized as an Office position.

Key Responsibilities

• Partner with your manager and stakeholders to translate open-ended business questions into an analytical approach, with clear deliverables that will directly translate to tangible benefits to revenue.
• 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 clever identification.
• Design experiments to improve how we price and operate across our different 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 your findings.
• Share your approach, results, and recommendations with technical and nontechnical audiences, and document your work for a clear handoff.

Requirements & Tech Stack

• Python or similar for data preparation, analysis, and model building.
• Ability to express statistical concepts clearly through pseudocode and think through edge cases when designing systems.
• AI tools to accelerate and expand work.

Qualifications

• Currently pursuing a Masters 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.
• Specifically, experience with time-series and causal analysis through coursework and research.
• Ability to explain analytical findings clearly and collaborate with diverse stakeholders, including non-technical audiences.
• Ability to move quickly and ambitiously without sacrificing attention to detail.
• Thoughtful problem-solving approach: check assumptions, validate results, and distinguish data support from uncertainty.
• Interest in applying quantitative methods to housing markets, business forecasting, and financial decision-making.