Senior Data Scientist, StreeyEasy

Zillow
Remote-USA$149k – $237kPosted 28 April 2026

Job Description

About the team StreetEasy, part of Zillow Group, helps people buy, sell, and rent homes across New York City and New Jersey with trusted listings, intuitive tools, and data-driven experiences. As part of this mission, the team uses data and technology to improve how consumers and partners discover opportunity in one of the most dynamic real estate markets in the country. About the role As a Senior Data Scientist at StreetEasy, you will help shape marketing strategy through experimentation, measurement, and data-driven insight. Embedded within the marketing team, you will work across initiatives such as A/B testing, lifecycle optimization, and marketing mix measurement to improve customer experience and drive high-quality traffic to StreetEasy’s websites and apps. This is a high-impact role for someone who enjoys connecting advanced analytics to clear business decisions and cross-functional action. You Will Get To Lead end-to-end experimentation for the marketing team, including A/B test design, analysis, and interpretation of results. Drive measurement approaches that improve marketing effectiveness, including marketing mix modeling and related performance analyses. Translate customer insights, metrics, and analytical findings into clear recommendations for technical and non-technical partners. Identify complex business problems, frame them clearly, and partner across teams to deliver scalable, data-informed solutions. Build reusable analytical frameworks, including simulations and causal inference approaches, to support broader team decision-making. Create dashboards and reporting in tools such as Tableau and Databricks to improve visibility into performance and opportunities. Partner with engineering to improve data quality, strengthen data collection, and build transformation pipelines using tools such as dbt. Mentor junior team members and champion data-informed decision-making across the organization. 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 $148,600.00 - $237,400.00 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 $141,200.00 - $225,600.00 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 Bachelor’s degree in Computer Science, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field, or equivalent practical experience. 5 years of experience using data to solve complex business problems in a professional environment. Strong proficiency in SQL and Python, or comparable programming experience, with experience using tools such as Tableau and Databricks. Experience designing, running, and interpreting experiments, with a strong foundation in statistical analysis and testing methodologies. Strong business acumen and product sense, with the ability to connect business goals to practical, data-driven recommendations. Excellent communication skills and experience working cross-functionally with partners across engineering, product, and marketing. Broad data scien ... (truncated, view full listing at source)
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