About the job

We support the Search Ads and Google Experience (SAGE) organization in developing the most important ad products at Google. These products are at the heart of Google’s business driving in annual growth and are advanced, and rapidly growing and evolving. We are also working on the most exciting projects related to AI (LLM Eval, AI Mode).Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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. 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, using specialized knowledge. 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 and upcoming data infrastructure.

• Own the process of gathering, extracting, and compiling data across sources via relevant 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.

Minimum qualifications

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.

• 3 years of 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 experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

• Experience working with Large Language Models (LLM’s) or Applied AI.