Job description

About the team You’ll join a collaborative Data Science team within Zillow’s Data Analytics and Insights organization, where we partner closely with Product, Engineering, and business teams to solve meaningful customer and business problems. Our team uses advanced analytics, experimentation, and machine learning to turn complex data into insights and scalable solutions that improve Zillow’s products and experiences. We value curiosity, thoughtful collaboration, and a shared commitment to using data to help people unlock life’s next chapter. About the role The Senior Specialist, Data Science applies advanced analytical methods and machine learning techniques to solve complex business problems, generate actionable insights, and improve Zillow’s products and customer experiences. The role independently drives end‑to‑end data science projects, partnering with cross‑functional teams to define problems, build and evaluate models, and translate findings into scalable, data‑informed decisions. You will get to Lead end‑to‑end data science projects from problem framing and hypothesis design through model development, validation, and deployment, ensuring solutions are aligned with strategic business goals and customer needs. Develop advanced statistical and machine learning models (for example, prediction, recommendation, or optimization) using large, complex datasets, and rigorously evaluate performance to improve accuracy, fairness, and robustness. Design and implement efficient data pipelines, feature engineering approaches, and experimentation frameworks in partnership with data engineering and product teams to enable scalable, repeatable analyses and model delivery. Translate complex quantitative findings into clear, compelling insights and recommendations for technical and non‑technical stakeholders, informing product roadmaps, operational decisions, and measurable business outcomes. Collaborate closely with product, engineering, analytics, and business partners to identify high‑impact opportunities, define success metrics, and prioritize data science work based on customer value and feasibility. Establish and advocate for best practices in data quality, model monitoring, documentation, and responsible AI usage, helping to continuously improve the reliability and trustworthiness of data‑driven solutions. Mentor less experienced team members by sharing domain knowledge, reviewing work, and contributing to a culture of learning, experimentation, and continuous improvement in data science methods and tools. 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, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia 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 Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field. 8 years of professional experience applying statistical analysis, machine learning, or advanced analytics to real‑world business problems in a data‑driven environment. Demonstrated experience working with large, complex datasets using programming languages such as Python or R and querying languages such as SQL. Experience designing and evaluating experiments or other causal inference approaches, and using metrics to assess model and product impact. Experience collaborating in cross‑functional settings (for example, with product, engineering, or operations teams) to deliver and operationalize data science solutions at scale. Or an equivalent combination of education and experience. 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.

Requirements

Must-haves

You will get to
Lead end‑to‑end data science projects from problem framing and hypothesis design through model development, validation, and deployment, ensuring solutions are aligned with strategic business goals and customer needs.
Collaborate closely with product, engineering, analytics, and business partners to identify high‑impact opportunities, define success metrics, and prioritize data science work based on customer value and feasibility.
Establish and advocate for best practices in data quality, model monitoring, documentation, and responsible AI usage, helping to continuously improve the reliability and trustworthiness of data‑driven solutions.
Mentor less experienced team members by sharing domain knowledge, reviewing work, and contributing to a culture of learning, experimentation, and continuous improvement in data science methods and tools.
Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field.
8 years of professional experience applying statistical analysis, machine learning, or advanced analytics to real‑world business problems in a data‑driven environment.
Demonstrated experience working with large, complex datasets using programming languages such as Python or R and querying languages such as SQL.
Experience designing and evaluating experiments or other causal inference approaches, and using metrics to assess model and product impact.
Experience collaborating in cross‑functional settings (for example, with product, engineering, or operations teams) to deliver and operationalize data science solutions at scale.
Or an equivalent combination of education and experience.
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.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaipythonsql

Platform: workday
Effort: long