Staff Data Scientist, ML Resource Efficiency & Impact

Google LLC; Sunnyvale (CA); On-site; USD 192,000 - 278,000; Full time

Job summary

Google Sunnyvale is hiring Share Staff Product Data Scientist, ML Resource Efficiency to optimize ML infrastructure and cost efficiency. You will analyze usage patterns, develop predictive models, and partner with Product, Finance and Engineering to drive data-informed decisions.

You will own end-to-end analyses, build robust data pipelines, and communicate insights to executives. A strong background in statistics, data science, and SQL is required, with excellent collaboration across teams.

Qualifications

• Bachelor's degree in a quantitative field (Statistics, Math, Data Science, Engineering, Physics, Economics)
• 10 years analytics experience with bachelor's or 8 years with a Master's, incl. coding in Python/R/SQL
• Experience articulating product questions and using statistics to inform decisions

Responsibilities

• Perform analysis using SQL, R, Python and provide analytical leadership
• Own outcomes from problem definition to metrics, data extraction, modeling and stakeholder presentation
• Develop solutions for ambiguous problems by framing hypotheses and recommendations
• Oversee cross-functional project timelines and drive process improvements
• Mentor colleagues and build capabilities in the specialization

Skills

Statistics

Data analysis

Python

SQL

R

Education

Bachelor's degree in quantitative field

Master's degree preferred

Tools

SQL

R

Python

SAS

Stata

MATLAB

Job description

Google Sunnyvale is hiring Share Staff Product Data Scientist, ML Resource Efficiency to optimize ML infrastructure and cost efficiency. You will analyze usage patterns, develop predictive models, and partner with Product, Finance and Engineering to drive data-informed decisions.

You will own end-to-end analyses, build robust data pipelines, and communicate insights to executives. A strong background in statistics, data science, and SQL is required, with excellent collaboration across teams.