Senior Product Data Scientist, ML Resource Efficiency

Google; Sunnyvale (CA); On-site; USD 163,000 - 236,000; Full time

Job summary

Google is seeking a senior data science professional to advance its ML compute efficiency across Google Cloud. You will analyze data, build scalable models, and partner with Capital Engineering, Finance, PMs, and executives to drive cost-effective deployment of ML resources globally.

You will shape analytics, pricing models, and service improvements while presenting findings to AI2 leadership and aligning with user needs across Platforms, Research, and PA PARM teams.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.

Responsibilities

• Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Help solve problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems to reach an optimal solution.
• Build new processes, procedures, methods, tests, and components with foresight to anticipate and address future issues.
• Report on KPIs to support business reviews with cross-functional leadership. Translate analysis results to business insights or product improvement opportunities.
• Build and prototype analysis and business cases iteratively to provide insights at scale. Develop knowledge of Google data structures and metrics, advocating for changes where needed for product development.
• Influence across teams to align resources and direction.

Skills

Analytics experience

Statistical analysis

Coding (Python, R, SQL)

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field

Tools

SQL

Python

R

Job description

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.

Minimum qualifications

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of 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 Machine Learning Infrastructure.

About The Job

Google's bespoke ML TPU infrastructure is a rapidly growing investment driving performance beyond Moore's Law. The Cloud ML Efficiency Data Science team provides insights and tools that enable product areas to efficiently consume ML resources for training and serving models.

In this high-visibility role, you will collaborate with Capital Engineering, Finance, PMs, and executive leadership to ensure the scalable and cost-effective deployment of ML compute across Google. Leveraging strong technical and analytical skills, you will uncover opportunities to improve efficiency through data transparency, software stack enhancements, user engagements, and service innovations like pricing and product tiers.

To succeed, you must be a strategic, agile problem solver who navigates ambiguity, acts with bias to action, and builds strong cross-functional relationships. You will partner closely with AI and Compute Enablement leads, regularly presenting findings to AI2 leadership.

Your work will directly, influence how Google optimizes investment, scaling ML infrastructure globally to meet the soaring demands of Google's ML products and research. You will engage with senior executives across Platforms, Research, Finance, and PA PARM teams to perfectly align our services with user needs.

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

Responsibilities

Learn more about benefits at Google .

• Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Help solve problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems to reach an optimal solution.
• Build new processes, procedures, methods, tests, and components with foresight to anticipate and address future issues.
• Report on Key Performance Indicators (KPIs) to support business reviews with the cross-functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
• Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.
• Influence across teams to align resources and direction.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .