Data Scientist

About the team The Marketing Analytics and Data Science (MADS) team is a well-established group responsible for measuring the performance of Zillow’s marketing initiatives and providing strategic counsel on optimization approaches. This team is tasked with constructing incremental measurement models and utilizing causal inference techniques to ascertain marketing effectiveness. MADS collaborates extensively with product marketing teams, advising them on strategic decisions informed by data. As a Data Scientist within Marketing Analytics & Data Science, the individual will join a collaborative unit focused on advancing Zillow’s mission by empowering the marketing organization to make optimal decisions through data-driven insights and recommendations. This is achieved through the development of causal and predictive models, as well as production-grade, scalable measurement solutions. The team's influence spans Marketing, Product, and Engineering, delivering models and pipelines that inform budget allocation, incrementality analysis, and growth strategy, to which the Data Scientist will contribute directly. We have a flat team structure and you will soon find yourself communicating directly with Senior Leadership. About the role At Zillow, Data Scientists develop insights and models that shape products and services, balancing rigor and speed, and ensuring outputs are methodologically sound and decision-useful. You Will Get To: Build and iterate on MMM and incrementality/attribution approaches, partnering with Marketing to turn measurement into action (budget allocation, channel strategy, performance forecasting). Design and apply causal inference methods (e.g., quasi-experiments, uplift/incrementality estimation), geo-testing and support online/offline experimentation where feasible. Develop and maintain scalable measurement infrastructure, data products and production model pipelines (feature engineering, feature generation, training/inference workflows, backtests, monitoring, observability), and contribute to reducing tech debt over time (reliability maintainability, durability). Partner cross-functionally to define success metrics, measurement plans, and decision frameworks; communicate results clearly to technical and non-technical audiences. Establish practical evaluation frameworks by partnering with other Data Scientists to ensure outputs are credible and reusable. 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 addition to a competitive base salary and benefits, this position is also eligible for equity awards based on factors such as experience, performance and location. Who you are Mandatory skills: 3-5 years of work experience involving quantitative data analysis, data science, complex problem solving. Prior experience in marketing analytics is a plus! 3 years of experience implementing a variety of measurement methods across modeling and testing for various marketing use cases Strong proficiency in SQL and Python (or R) and 3 years or more of experience as a data scientist experience querying multi-terabyte-sized noisy data sets such as clickstream data. A strong understanding of statistical concepts, modeling and inference, A/B testing, measurement methods, and causal inference techniques as it relates to the marketing space. Experience in modeling techniques like regression, forecasting or more complex modeling approaches (like xgboost, random forest, Bayesian ML) and delivering analyses that are repeatedly used by business over months. Ability to work cross-functionally and strong written, verbal, and visual communication skills. Nice to have: Possess a profound understanding of various drivers, forms of attribution methods, and measurem ... (truncated, view full listing at source)