Data Scientist, Trust & Safety - Rentals

About the team

The Data Science team at Zillow turns complex data into insights, models, and products that help power smarter decisions across the business. As part of our broader Data Analytics and Insights organization, this team partners closely with product, engineering, and business leaders to solve meaningful problems, improve the quality and usability of our data, and build scalable solutions that create impact for customers and employees alike.

We’re a collaborative, curious group that values thoughtful experimentation, continuous learning, and using data responsibly to move Zillow forward.

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. In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $ - $ annually.

This base pay range is specific to these locations and may not be applicable to other locations. In Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia the standard base pay range for this role is $ - $ annually. The base pay range is specific to these locations and may not be applicable to other locations.

In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

• With guidance from your manager, lead the design, development, and deployment of end-to-end analytical and machine learning solutions that address moderately complex business problems and customer use cases.
• Partner with product, engineering, and business stakeholders to frame ambiguous questions into testable hypotheses, define success metrics, and translate requirements into robust analytical or modeling approaches.
• Build, validate, and maintain scalable data pipelines, features, and models using modern data and ML tooling, ensuring reliability, reproducibility, and performance in production environments.
• Analyze large, complex datasets to uncover trends, drivers, and opportunities, and clearly communicate findings and recommendations to technical and non-technical audiences.
• Apply sound experimentation and evaluation practices (e.g., A/B testing, backtesting, error analysis) to measure impact, compare alternatives, and guide iteration on models and data products.
• Contribute to shared standards, documentation, and best practices for data quality, model governance, and responsible use of data and AI within the Data Science community at Zillow.

• Bachelor’s degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
• 5+ years of experience applying data science, advanced analytics, or machine learning in a professional setting.
• Experience designing and implementing end-to-end analytical or ML solutions, including data preparation, feature engineering, model development, validation, and operationalization.
• Experience working with large datasets and modern data ecosystems (e.g., distributed data processing, cloud-based data platforms) to develop insights and data products that support business decisions.
• Experience collaborating with cross-functional partners to understand requirements, prioritize work, and deliver measurable outcomes using data and analytics.
• Or an equivalent combination of education and experience.

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, and design, you’ll be part…