Senior Product Data Scientist, ML Resource Efficiency

About the role

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

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

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 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.