Senior Data Scientist, Product, AI Context Engineering

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Minimum qualifications:

* Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience.

* 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 years work experience with a Master's degree).

Preferred qualifications:

* Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

* 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).

* Experience working on a consumer facing product or quality evaluations preferred.

* Demonstrated ability to convey information clearly and concisely, both verbally and in writing, with a focus on drawing out key implications and actionable insights.

About the job

If you'd like to stay at the epicenter at Google Search and pioneer the next era of our search products, you've come to the right team.

As a Data Science team that supports Core Ranking and AI Context Engineering (CRAFT), we are the foundation for all of Google's key products, Search, AI Overview, and AI Mode. You will work alongside engineers and product managers, address the most complex issues, push the boundaries of Web and AI quality, and architect novel ways for billions of users to experience Google's capabilities on a daily basis as this is your chance to define State-of-the-Art (SOTA) Search products for Google.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $163000 - $237000 (USD) + 15% bonus target + bonus + equity + benefits

Learn more about benefits at Google.

Responsibilities

* Collaborate closely with Engineers and Product Managers to identify quality and metric headrooms.

* Conduct analyses of large-scale datasets, apply statistical/AI methods to solve problems, and present actionable insights and recommendations to various stakeholders.

* Build evaluations and measurements to guide hillclimbing and iterative improvements, and automate these evaluations and measurements in partnership with Engineering and Product teams.

* Function as an integrated partner to impel system changes and launches.