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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
New York, NY, USA; San Jose, CA, USA.
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.
About the jobIn this role, you will be in a team that applies statistical excellence and data science to understand AI opportunities and the developer productivity at a scale as large as that of Google. As a Data Scientist on the Developer AI team, you will be at the vanguard of using advanced data science and machine learning to comprehend and address the most significant hurdles our software engineers face. You will work with a vast and intricate dataset of developer activities. Your insights will directly influence the next wave of AI-enhanced tools for every developer at Google. You will have a passion for data, AI, and creating a substantial real-world impact.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $253000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Collaborate with engineering teams to instrument and gather high-quality data, laying the groundwork for understanding and enhancing AI products and developer productivity.
- Perform deep analysis of developer processes and challenges to pinpoint where AI-driven solutions can deliver the most significant impact.
- Create and monitor key performance indicators to measure the value and influence of our products on Google's developers.
- Move beyond reactive data analysis to discover latent trends, forecast future requirements, and prove the return on investment of our projects.
- Present your discoveries and insights to leadership, guiding data-centric decisions that will define the future of developer tools at Google.
