Data Scientist

Zillow

3d•$119,600 - $201,100•Remote

About The Position

The Partner Analytics team within Business Data is hiring a Data Scientist to lead analytics to uncover insights to drive both better business decisions and customer experiences across our product portfolio. 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.

Requirements

Bachelor’s degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
5+ years of experience applying data science, advanced analytics, or machine learning in a professional setting.
Experience designing and implementing end-to-end analytical or ML solutions, including data preparation, feature engineering, model development, validation, and operationalization.
Experience working with large datasets and modern data ecosystems (e.g., distributed data processing, cloud-based data platforms) to develop insights and data products that support business decisions.
Experience collaborating with cross-functional partners to understand requirements, prioritize work, and deliver measurable outcomes using data and analytics.
Or an equivalent combination of education and experience.

Responsibilities

Lead the design, development, and deployment of end-to-end analytical and machine learning solutions that address moderately complex business problems and customer use cases.
Partner with product, engineering, and business stakeholders to frame ambiguous questions into testable hypotheses, define success metrics, and translate requirements into robust analytical or modeling approaches.
Build, validate, and maintain scalable data pipelines, features, and models using modern data and ML tooling, ensuring reliability, reproducibility, and performance in production environments.
Analyze large, complex datasets to uncover trends, drivers, and opportunities, and clearly communicate findings and recommendations to technical and non-technical audiences.
Apply sound experimentation and evaluation practices (e.g., A/B testing, backtesting, error analysis) to measure impact, compare alternatives, and guide iteration on models and data products.
Contribute to shared standards, documentation, and best practices for data quality, model governance, and responsible use of data and AI within the Data Science community at Zillow.