Staff Data Scientist, Search AI Overview
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Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
- 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.
Preferred qualifications:
- 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
- 3 years of experience as a people manager within a technical leadership role.
About the job
The mission of the Search AI Overview Data Science team is to leverage data, measurement methodologies, analysis insights, and modeling to help improve Search experience. You’ll be working closely with a team of developers and product managers, delivering on a roadmap focused on revolutionizing the Google Search experience with the latest GenAI model capabilities. Your analysis will help communicate user needs, unlock new use cases and ways of how users interact with Google Search on a daily basis.
In 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: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead and drive cross-functional development with a wide variety of teams, and work closely with product managers and engineers to identify growth and quality opportunities for the product.
- Conduct analyses of large-scale datasets, applying statistical methods to solve complex problems, and presenting recommendations to stakeholders. Influence product development, improve user experiences, and drive business outcomes.
- Drive understanding, evaluate, and develop measurement methodologies for complex GenAI models.
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