Manager, Data Science

Zillow

2d•$152,500 - $256,500•Remote

About The Position

As a Manager of Data Science within Rentals Analytics, you’ll lead a team at the heart of Zillow’s fastest-growing business. The Rentals Shopping pillar is dedicated to revolutionizing how millions of renters discover and secure their next home. Your team delivers the analysis, experimentation, and modeling that drives product decisions across the shopping funnel—from search and discovery through applications and lease signing. This team’s impact spans Product, Engineering, and Business Strategy, and the Manager will build and lead a high-performing team that directly shapes the future of the rental shopping experience. Zillow Group is seeking a Manager of Data Science to lead measurement, experimentation, and insight generation for the Rental Shopping pillar. With Rentals revenue up 45% year-over-year and tens of millions of monthly unique visitors, this is a rare opportunity to lead a data science team at the intersection of consumer product development and rapid business growth. You will set the technical direction for how we measure, test, and optimize every stage of the renter’s journey—turning statistical rigor into product innovation and business impact at scale. This is a people leadership role first, with meaningful technical depth. You will be responsible for: Setting the technical direction and measurement strategy for the shopping funnel Developing and mentoring data scientists across experimentation, causal inference, and product analytics Defining scalable frameworks for A/B testing, funnel optimization, and consumer behavior modeling Influencing senior product and business stakeholders with data-driven recommendations Ensuring analytical rigor translates into tangible product improvements and business growth This is an opportunity to grow your career as a Data Science leader while helping shape the future of rental shopping at Zillow. You’ll collaborate across teams to solve meaningful challenges that directly impact how people move through one of life’s biggest milestones. As a Manager of Data Science, you’ll bring your expertise and curiosity to a team that values progress, purpose, and forward momentum—for both our customers and your career.

Requirements

6+ years of experience in data science, applied science, product analytics, or consumer analytics.
2+ years of experience mentoring or directly leading data scientists
Direct experience working in a consumer-facing product environment, with ownership of experimentation, funnel measurement, or product analytics at scale
Strong understanding of A/B testing, causal inference, funnel optimization, and consumer behavior modeling
Experience working with large-scale behavioral, clickstream, or marketplace datasets
Deep proficiency in SQL and Python
Experience partnering cross-functionally with Product, Engineering, and Design stakeholders
Strong executive communication skills with the ability to influence senior leadership decisions
Experience integrating experimentation, observational causal methods, and predictive modeling into coherent measurement frameworks
Demonstrated ability to adopt AI-enabled tools thoughtfully while maintaining rigor and governance

Nice To Haves

Experience in rental, real estate, or marketplace platforms
Experience scaling experimentation programs across multiple product surfaces
Exposure to recommendation systems, search ranking, or personalization analytics
Familiarity with Databricks, Snowflake, Airflow, dbt, or similar infrastructure tools
Understanding of privacy shifts and their impact on consumer analytics and measurement

Responsibilities

Define and scale the measurement foundations for Zillow’s rental shopping experience.
Establish the long-term measurement strategy for the shopping funnel: search, discovery, listing engagement, applications, and lease conversion.
Define experimentation frameworks that scale across markets, product surfaces, and renter segments.
Design incrementality and lift testing standards to quantify the impact of product changes on renter outcomes.
Partner with Product leadership to define KPIs that balance renter experience quality with business growth.
Ensure measurement systems are credible, scalable, and integrated into the product development lifecycle.
Lead the proactive discovery of data-driven opportunities that define future product bets.
Drive deep-dive analyses of renter behavior, market dynamics, and funnel performance to identify high-impact growth opportunities.
Oversee integration of experimentation, causal inference, and predictive modeling into a coherent insights framework.
Partner with Product, Engineering, and Design leaders to translate complex analytical findings into actionable product strategies.
Connect consumer behavior insights to business outcomes such as lead quality, conversion rates, and revenue growth.
Manage and develop a team of data scientists working across shopping funnel measurement and consumer analytics.
Set clear expectations for scope, quality, and business impact.
Coach team members in technical rigor, structured thinking, and executive communication.
Conduct high-quality performance reviews and career development planning.
Create an inclusive, high-accountability team culture.
Drive hiring strategy to build depth in experimentation, product analytics, and consumer modeling.
Contribute technically to ambiguous or high-leverage problems, and consistently demonstrate execution by delivering hands-on work and leading by example.
Raise the bar on production-grade analytics and experimentation.
Ensure experimentation frameworks are reusable and scalable across shopping product surfaces and renter segments.
Guide development of production-ready modeling pipelines (versioning, monitoring, governance).
Reduce technical debt in legacy measurement and analytics workflows.
Partner with Data Engineering to improve data reliability and infrastructure for shopping funnel data.
Balance rigor with speed—choosing appropriate methodological complexity based on decision stakes.
Operate as a strategic thought partner to senior stakeholders across Product, Engineering, and Business Strategy.
Communicate insights clearly to VP and executive audiences.
Translate technical findings into product strategy and investment implications.
Influence roadmap decisions across the shopping pillar and adjacent product areas.
Prioritize team work based on enterprise-level impact.
Connect renter behavior insights with marketplace dynamics and business outcomes.
Proactively shape strategy—not just respond to requests.
Lead thoughtful adoption of AI within your team.
Encourage responsible use of AI-assisted coding and analytics tools to improve productivity.
Establish guardrails to protect rigor, data integrity, and governance.
Identify workflows where automation meaningfully improves experimentation velocity and insight generation.
Evaluate emerging tooling that strengthens scalability without compromising quality.