About the job
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.
Responsibilities
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.
Qualifications
Minimum
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.
Preferred
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.