Senior Data Scientist

Zillow

18d•$141,200 - $237,400•Remote

About The Position

Zillow Group's Business Data organization is seeking a Senior Data Scientist to be a core analytics lead for Zillow's broker data products, measurement strategy, and enterprise ROI. This role involves 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 causal inference frameworks to measure product, go-to-market, and business impact at the enterprise level. You will also build scalable analytical foundations to transform complex data into actionable insights. The data products you build 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, offering a rare opportunity to build a high-visibility charter from the ground up. Your insights will directly shape how Zillow invests in one of its biggest strategic areas, and you will see your work quickly influence decisions, product direction, and the value Zillow delivers to its partners. This role is an individual contributor position with no direct reports, working within a broad data organization that creates opportunities for cross-domain learning and influence.

Requirements

5+ years of experience in data science, product analytics, or a related quantitative field
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
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
Ability to work independently in ambiguous spaces as a self-starting, end-to-end owner

Nice To Haves

A Master's degree (or equivalent experience) in statistics or a similar quantitative discipline is preferred
B2B product and business strategy experience are a plus
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
Data visualization experience (e.g., Tableau) is preferred but not required

Responsibilities

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