Minimum qualifications:- Bachelor'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) or 5 years of 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).
About the jobThe Contextual Search Data Science team is at the forefront of shaping the future of search. Our mission is to deeply understand and enhance user experiences by leveraging contextual data. We drive product strategy and innovation for some of Google's most critical Search surfaces, ensuring our AI-first features are intuitive, effective, and power new ways for users to find exactly what they need in the moment.
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: $163000 - $236000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities- Delve deep into user behavior patterns, identifying opportunities for growth, and understanding the end-to-end user journey across our contextual search surfaces.
- Design, implement, and analyze A/B tests and other experiments to measure the impact of new contextual features and product changes, ensuring data-driven decisions.
- Build and refine the tools, pipelines, and best practices our team uses, while staying at the forefront of AI techniques to enhance our analytical capabilities.
- Guide complex, ambiguous projects from inception to completion, influence cross-functional roadmaps alongside Engineering and Product partners, and mentor junior data scientists on the team.
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