Senior Data Scientist, Web Quality and AI Context Engineering

As a Data Scientist on the team at the core of Google Search, you will provide the foundational insights that power our flagship products, including Search, AI Overviews, and Gemini in Search. You will support the team in critical areas such as Core Web Quality (Indexing, Retrieval, Ranking), News and Freshness, and AI Context Engineering (CRAFT). In collaboration with engineers and product managers, you will address complex challenges at the intersection of web and AI quality, architecting state-of-the-art approaches that redefine how billions of users access Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
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Minimum qualifications
Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.

Preferred qualifications
8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
Past experience working on a consumer facing product or quality evaluations preferred.
Ability to apply appropriate quantitative models to real-world business problems, and solid experience with experimental design and analysis, survey design, evaluation methodologies, statistical modeling and machine learning algorithms.
Demonstrated ability to convey complex information clearly and concisely, both verbally and in writing, with a focus on drawing out key implications and actionable insights.

Responsibilities
Collaborate closely with Engineers and Product Managers to identify quality and metric headrooms.
Conduct rigorous analyses of datasets, apply statistical/AI methods to solve complex problems, and present actionable insights and recommendations to various stakeholders.
Develop evaluations and measurements to guide hillclimbing and iterative improvements; and automate them in collaboration with Engineering and Product.
Serve as an integrated partner to impel system changes and launches.