Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  
• 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
  

Preferred qualifications:

• 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 a PhD degree.
  

About the job

The team supports the SAGE (Search Ads and Google Experience) organization in developing important ad products at Google from classic text ads, to rich shopping ads, to exciting new products like Discovery ads.

The US base salary range for this full-time position is $127,000-$187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

• Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer, and provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  
• Use custom data infrastructure or existing data models as appropriate, design and evaluate models to mathematically express and solve defined problems with limited precedent.
  
• Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing/upcoming data infrastructure.
  
• Own the process of gathering, extracting, and compiling data across sources via tools (e.g., SQL, R, Python), format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
• Research, develop, and maintain metrics for Search Ads (e.g., A/B tests, experimentation).