About the roleBroker and brokerage partnerships are a strategic focus for Zillow and one of the biggest growth opportunities in residential real estate. Brokers sit at a critical distribution level, and Zillow is investing in new products and programs to unlock the full potential of these partnerships. Robust measurement and strategic guidance will power what comes next: understanding where value is created, what's working, and where to invest.
The Business Data team is hiring a Senior Data Scientist to serve as a core analytics lead for Zillow's broker data products, measurement strategy, and enterprise ROI, turning on the lights to the depth and value of broker relationships across the Zillow Group ecosystem. You will lead the design of broker-level success metrics and the causal inference frameworks that measure product, go-to-market, and business impact at the enterprise level, and build the trusted, scalable analytical foundations that turn complex data into insights decision-makers act on. The data products you build won't just inform internal decisions; they will help Zillow deliver more value to broker partners and their customers. This is a newly formed pod with significant company investment and executive visibility: few roles offer this much influence over how a strategic priority is measured, understood, and grown.
This work is highly visible to senior leadership, and your insights will directly shape how Zillow invests in one of its biggest strategic areas. For a data scientist ready to grow, this is a rare opportunity to build a high-visibility charter from the ground up, with a clear runway to expand your scope, influence senior leaders, and sharpen your craft alongside a broad data organization working across AI-enabled analytics, data products, and measurement. You will see your work show up quickly in decisions, product direction, and the value Zillow delivers to its partners.
What you'll do- Serve as the high-context analytics owner for broker data products and go-to-market, establishing durable methodology and metric standards
- Independently scope and deliver end-to-end measurement and data science projects, from problem framing through methodology design, validation, and productionization
- Lead the design of broker-level success metrics and causal inference frameworks (e.g., matching, difference-in-differences) that quantify the impact of products, features, and go-to-market initiatives at the enterprise level
- Partner with Product Managers and go-to-market teams to design, deploy, and execute measurement roadmaps, guiding data product development from problem definition through measurement and iteration
- Conduct analytical deep dives and opportunity sizing to inform product and go-to-market roadmaps; Provide data-driven recommendations to senior leadership, clearly communicating trade-offs, assumptions, and impact
- Build reliable, scalable analytical pipelines, scheduled jobs, and reusable data products that scale insights and demonstrate product value to partners and customers; Leverage AI-assisted analytics workflows to scale your impact, while designing core analytical logic in deterministic, verifiable ways
- Support externally facing product value narratives with rigorous, defensible methodology
Scope & impact- Pioneering Senior Data Scientist at the center of Zillow's broker data product and go-to-market strategy, with executive visibility and sponsorship
- Owns broker measurement and data product analytics end to end, delivering solutions with limited oversight
- Shapes the metrics, measurement approaches, and methodology standards that make broker data products trusted and actionable across the org
- Balances speed and rigor, making sound trade-offs in measurement, analysis, and stakeholder alignment
- Individual contributor role with no direct reports, working within a broad data organization that creates meaningful opportunities for cross-domain learning and influence
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 $148,600.00 - $237,400.00 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 $141,200.00 - $225,600.00 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.
Who you areYou are energized by ambiguous, high-impact problems and love turning complex data into decisions people trust. You hold a high bar for analytical rigor, enjoy partnering across functions, and take pride in seeing your insights change what a business does. You appreciate the unique challenges of building and measuring B2B products and go-to-market.
Additionally, we expect you to have:
- 5+ years of experience in data science, product analytics, or a related quantitative field; a Master's degree (or equivalent experience) in statistics or a similar quantitative discipline is preferred
- Strong foundation in statistics, causal inference, and experimentation (A/B testing), with high analytical rigor and demonstrated ability to design clear, durable metrics and assess product or go-to-market impact from definition through decision-making
- Strong stakeholder management skills, including experience partnering with Product Managers, engineers, and go-to-market teams, influencing decisions, and communicating complex findings to technical and non-technical audiences; B2B product and business strategy experience are a plus
- Strong SQL and Python skills, including the ability to develop and maintain complex query logic; comfortable working with large datasets in modern data platforms (e.g., Spark, Databricks)
- Effective at leveraging AI tools in day-to-day analytical work while maintaining high rigor
- Experience with product analytics at a senior level, including measurement, experimentation, clickstream and segment analysis, and influencing decisions with data; experience building end-to-end predictive ML models is a strong plus
- Experience building reliable, scalable analytical pipelines and scheduled data jobs, or contributing to data and analytics platform development, is a plus
- Ability to work independently in ambiguous spaces as a self-starting, end-to-end owner; data visualization experience (e.g., Tableau) is preferred but not required
