Senior Data Scientist, Experimentation & AI Measurement

The Zillow Experimentation Platform (ZEXP) team enables Zillow Group's Product, Engineering, and Data Science organizations to test bold ideas, validate strategies, and make trustworthy decisions quickly. Our mission is to make rigorous, self-service experimentation and measurement possible for anyone — regardless of their role — through powerful tools, clear guidance, and scientific rigor.

We're part of the Core Data Tech organization, partnering with engineers, data scientists, and machine learning practitioners to scale experimentation and measurement across the Zillow ecosystem. Our work fuels Zillow's Housing Super App strategy by enabling fast, safe, and accurate decision-making rooted in trustworthy data.

Learn more about what we're building at

As a Senior Data Scientist working in ZEXP, you'll deliver value through your analyses and by elevating the work of the team around you. You'll bring statistical rigor to two connected problems: making Zillow's experimentation practice more self-service and trustworthy, and measuring whether Zillow's growing investment in AI-assisted engineering and development tools creates durable, high-quality value rather than just activity.

This is an experienced individual-contributor role that blends hands-on measurement, causal inference, and applied statistics with team leadership. You'll act as a focal point for projects, mentor other scientists and analysts, and represent data science and experimentation to partner teams — advocating for sound measurement wherever decisions get made. You'll balance depth and speed in an environment of competing priorities, and you'll know when further rigor stops adding value.

You will get to

• Design, build, and validate statistically rigorous methods for experiment design and analysis — product ionizing techniques such as variance-reduction and sequential testing as reusable, self-service platform capabilities.
• Build and improve automated guardrails that prevent the common causes of experiment restarts and manual interventions — in-flight monitoring and alerting, ramp-plan adherence, early-stopping thresholds, and cross-line-of-business guardrail-harm checks — in support of reliable and trustworthy experimentation practices.
• Lead experiment design reviews for high-visibility launches, catching issues like ill-suited experimental populations, misaligned hypotheses, or contradictory launch criteria, protecting Zillow's biggest decisions from flawed experimental practices.
• Define and scale a measurement framework for AI's impact on engineering and behavior — segmenting usage and proficiency at the team and org level, and connecting adoption to behavioral change, productivity, quality, and financial outcomes.
• Pair velocity signals with lagging quality measures (reverts, change-failure rate, MTTR, defects, maintainability) so that speed gains are never mistaken for net value.
• Apply causal-inference thinking to AI product and tooling measurement — establishing sound, defensible methods for measuring whether AI investments deliver real value.
• Turn complex analyses into leadership-ready narratives and self-service insight experiences that partners can explore on their own.
• Mentor junior scientists and analysts on the core data science toolkit, share best practices across the team, and lead work streams end to end.

This role has been categorized as a teleworker position. Teleworkers 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. Employees may live anywhere in Mexico, with availability to travel to Mexico City, as we recommend attendance at occasional office events.

In addition to a competitive base…