The Staff Product Data Scientist for ML Resource Efficiency at Google will focus on enhancing the efficiency of machine learning infrastructure through rigorous analysis and strategic insights. This role involves collaborating with various stakeholders, including senior executives, to optimize resource allocation and improve service alignment with user needs. The position requires a blend of analytical expertise and product-specific knowledge to drive impactful decisions. The team aims to support the scalable and reliable deployment of ML compute resources across Google.

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding, or 8 years of work experience with a Master's degree.
• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field is preferred.
• 13 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding, or 10 years of work experience with a Master's degree.
• Experience with databases, data warehouses, and business intelligence and analytical tools.

• Perform analysis utilizing relevant tools such as SQL, R, and Python.
• Provide analytical thought leadership through proactive and strategic contributions.
• Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, and presentation to stakeholders.
• Develop solutions and manage ambiguous problems by framing issues and making recommendations.
• Oversee the integration of cross-functional project timelines and develop process improvements.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.