Senior Data Scientist

Zillow

14d•$141,200 - $237,400•Remote

About The Position

The Partner Analytics team within Business Data is hiring a Senior Data Scientist to lead analytics to uncover insights to drive both better business decisions and customer experiences across our product portfolio. Zillow Group’s Business Data organization represents the next step forward in the company's dedication to integrate an improved set of B2B agent software & advertising products for customers and partners, their clients, and the real estate industry as a whole. Zillow has built and acquired a portfolio of market-leading products for agent productivity, listing media, showing coordination, transaction management and analytics solutions. Our wide array of products and services are built on technological innovations crafted to bring efficiencies to all users.

Requirements

4–7+ years of experience in data science, applied machine learning, or a related field
Strong foundation in statistics, machine learning, and experimentation, with demonstrated ability to apply methods to real-world business problems
Proficient in Python (pandas, scikit-learn, PySpark) and SQL; comfortable working with large datasets in modern data platforms (e.g., Snowflake, Spark)
Experience building segmentation and performance models and translating outputs into business insights
Familiarity with production workflows (e.g., Airflow, dbt, model deployment patterns, monitoring)
Ability to work independently in ambiguous spaces while maintaining alignment with stakeholders
Strong communication skills, with the ability to tailor insights to technical and non-technical audiences
Experience collaborating across multiple product and business teams

Responsibilities

Independently scope and deliver end-to-end data science projects, from problem framing through model development, validation, and productionization
Build and maintain industry performance and customer segmentation models, applying appropriate techniques (e.g., clustering, regression, tree-based models) and ensuring they are robust, interpretable, and actionable
Partner with Data Engineering and ML Engineering to deploy and maintain models in production, including feature development, batch/real-time scoring, and monitoring model performance over time
Design and analyze experiments and observational studies (A/B testing, causal inference) to evaluate product features and business initiatives
Translate ambiguous business problems into well-defined analytical approaches, selecting appropriate methodologies and success metrics
Provide data-driven recommendations to senior leaders, clearly communicating trade-offs, assumptions, and impact
Collaborate with cross-functional teams including Follow Up Boss, Preferred, and zPro to align on goals, define KPIs, and deliver integrated insights
Contribute to scalable data assets (clean datasets, metrics definitions, dashboards) that enable self-service analytics
Mentor junior team members and contribute to team best practices, code quality, and documentation.