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Data Scientist

Roles & Responsibilities

  • 3-5 years of experience in quantitative data analysis or data science with complex problem solving (marketing analytics a plus)
  • Strong proficiency in SQL and Python (or R) with 3+ years of experience querying multi-terabyte noisy data (e.g., clickstream)
  • Solid grounding in statistics, modeling/inference, A/B testing, measurement methods, and causal inference in marketing
  • Experience with modeling techniques (regression, forecasting, XGBoost/Random Forest/Bayesian methods) and delivering analyses used by business over time

Requirements:

  • Build and iterate MMM and incrementality/attribution approaches with Marketing to drive budget allocation, channel strategy, and performance forecasting
  • Design and apply causal inference methods (quasi-experiments, uplift/incrementality estimation), geo-testing, and support online/offline experiments when feasible
  • Develop and maintain scalable measurement infrastructure, data products, and production model pipelines (feature engineering, training/inference workflows, backtests, monitoring, observability)
  • Partner cross-functionally to define success metrics and decision frameworks; communicate results clearly to technical and non-technical audiences; establish practical evaluation frameworks with other Data Scientists

Job description

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 measurement mechanisms within the marketing domain.

  • Demonstrate comprehension of the evolving privacy landscape and its impact on the marketing measurement ecosystem.

  • Experience utilizing tools such as Databricks, Snowflake, Looker, Tableau, Airflow, or Fivetran.

  • A Ph.D. in a quantitative field (e.g., science, engineering, mathematics) or equivalent professional experience is required.

  • Proficiency in agile methodologies and familiarity with the Jira tool.

  • Familiarity with data engineering tools and platforms.

  • Experience working with clickstream data.

  • Direct, hands-on experience with Marketing Mix Modeling (MMM), media/marketing analytics, budget optimization, or incrementality measurement.

  • Experience applying causal inference in business contexts (e.g., quasi-experimental designs, uplift modeling, synthetic controls, difference-in-differences) and/or A/B experimentation.

  • Practical skills in MLOps, encompassing the construction of repeatable pipelines, model versioning, monitoring, reproducibility, and operation within a shared codebase.

  • Practical skills and experience with DBT pipeline development.

  • Familiarity with visualization techniques and the ability to articulate data-driven narratives to stakeholders using appropriate visualization tools.

Get to know us

At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company that's reshaping an industry and helping more people make home a reality.

Zillow is honored to be recognized among the best workplaces in the country. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025, and included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.

No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.


Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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