Sr. Applied Scientist 20

About the team

As a Senior Applied Scientist on Zillow Group's Conversion and Core Modeling team, you will help build a unified, observable, and explainable decision framework for Zillow's core For Sale marketplace. This team sits at the center of revenue-driving experiences, where automated systems make confident decisions under uncertainty while balancing short-term transaction performance with long-term program value.

About the role

You are a systems thinker experienced in both optimization and production machine learning. You will buildand scale routing and allocation decision systems that match Zillow consumers with trusted partners in our core marketplace, improving performance while increasing transparency and explainability in our automated systems.

You will get to:

• Iterate on optimization frameworks in constraint-driven, multi-objective environments to balance customer experience and long-term business value.

• Build and productionize ML-driven routing systems for large-scale marketplace decision systems, owning models across the full lifecycle from feature design through deployment and monitoring.

• Work directly with partner teams (such as product, engineering, and operations) to clarify system behavior, communicate tradeoffs, and align on decision policies.

• Uphold high standards for production quality, including reliability, observability (dashboards, diagnostics, automated monitoring), and operational readiness for critical decision services.

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 $160,900. 00 - $257,100. 00 annually. This base pay range is specific to these locations and may not be applicable to other locations. In Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range for this role is $152,900. 00 - $244,300. 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 are• 5+ years of applied science experience (industry or equivalent), including work on optimization-driven or constraint-based decision systems such as dispatch, matching, scheduling, or routing, with measurable business impact.

• 3+ years owning production machine learning systems end to end, across the full model lifecycle from feature design and training through validation, deployment, and monitoring.

• Proficient in Python and SQL for building, evaluating, and deploying models in production environments.

• Advanced degree (MS or PhD) in a quantitative field (for example, Economics, Operations Research, Data Analytics, Statistics, or a related discipline), or equivalent practical experience in applied science or other data-intensive roles.

• Strong mathematical and algorithmic reasoning skills, including comfort working with multi-objective tradeoffs, constraints, and uncertainty.

• Strong software engineering fundamentals, including development best practices, testing, and operational rigor in production environments.

• Experience building transparent, explainable systems and clearly communicating decision logic to both technical and non-technical stakeholders.

• You pair curiosity with structured problem-solving to uncover new opportunities and areas of improvement and take initiative to develop practical, data-informed solutions.

• Here at Zillow - we value the experience and perspective of candidates with non-traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences.

Nice to have:

• Experience building or optimizing large-scale marketplace decision systems (for example, rideshare, delivery, travel, e-commerce, or logistics platforms).

• Experience applying mathematical optimization techniques (such as constraint-based optimization, linear or integer programming, or stochastic optimization) in production decision systems.

• Experience designing and implementing observability for decision systems, including dashboards, diagnostics, automated monitoring, and alerting for model and business performance.

Get to know us

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 cust