Senior Data Scientist, Search AI Frontier Experience
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.
- Experience working on a consumer facing product.
About the job:
This is an exciting opportunity to work on the fast evolving AI space for Google Search, namely AI Frontiers. You’ll be working closely with a strong team of senior engineers and product managers, and delivering on a roadmap aimed at super charging the Google Search experience with the latest GenAI model capabilities and unlock new use cases or ways of how users interact with Google search on a daily basis.
The mission of Search AI Frontier Experience Data Science team is to leverage data, measurement methodologies, analysis insights and modeling to help push the frontiers of Search in the context of latest GenAI capabilities and unlock new ways/use cases on how users interact with Google search.
The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Responsibilities:
- Interact cross-functionally with a wide variety of teams, and work closely with Product Manager and Engineer leads to identify growth and quality opportunities for the product.
- Conduct analyses of large-scale datasets, applying statistical methods to solve complex problems, and present actionable recommendations to stakeholders.
- Understand, evaluate, and develop measurement methodologies for complex GenAI models.
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