About the role

As a Sr. Applied Scientist, you will help drive the next generation of ranking, recommendation, and generative AI systems for Zillow's home-shopping experience. Your work will directly impact how millions of users discover and shop for homes, as you research, design, and deploy innovative machine learning models that power key product features. You'll collaborate across disciplines to deliver solutions that make home shopping more intuitive, personalized, and efficient.

You will get to

• Lead the end-to-end design, development, and deployment of applied machine learning models and algorithms, from problem formulation and data exploration through experimentation, evaluation, and productionization.
• Architect robust, scalable pipelines for data preparation, feature engineering, model training, and model serving in partnership with data and software engineering teams.
• Conduct rigorous offline analyses and online experiments to evaluate model performance, interpret results, and recommend data-driven improvements to product experiences and business metrics.
• Collaborate with product, engineering, and analytics partners to translate ambiguous business needs into clear scientific requirements and technical roadmaps, aligning work with customer and company goals.
• Implement and champion responsible AI practices, including model monitoring, fairness and bias checks, and continuous improvement of models in production.
• Mentor and coach other applied scientists and engineers by reviewing designs, sharing best practices, and guiding the adoption of modern machine learning techniques 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 $160,900.00 - $257,100.00 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 $152,900.00 - $244,300.00 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, Mathematics, Electrical Engineering, or a related quantitative field.
• 8+ years of experience applying machine learning or advanced statistical modeling in an industry setting, including delivering models into production environments.
• Proven experience working with large-scale data sets, experimentation or A/B testing, and model performance measurement in support of consumer or enterprise products.
• Demonstrated success collaborating in cross-functional teams to turn data and research insights into shipped features or operational improvements.
• Or an equivalent combination of education and experience.