Minimum qualifications:

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

Preferred qualifications:

• 8 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

Google is one of the pioneers of modern digital advertising, and the enabler of a thriving and open internet advertising ecosystem that supports users, publishers, and advertisers. Modern digital advertising is a scaled business that relies on a mutually-reinforcing cycle of ad-sales, ad-planning, ad-implementation/optimization and ad-measurement. Ad-measurement is key to this cycle, and consequently is critical to the business. Among other things, good measurement helps advertisers and platforms to conceptualize, create and plan successful campaigns; to serve the right ads to the right users; to help allocate resources to the right channels and to allocate bids in auctions and budgets across campaigns appropriately; and to audit the efficacy of ads in delivering on various campaign goals. Good measurement is also key for ensuring users are exposed to ads they find useful; and for ensuring publishers, content creators, and other ad-tech firms can monetize their content appropriately; both of which are key to sustaining an open and vibrant internet.

Google's advertising measurement team focuses on combining data at scale with formal science to make this possible. Our science helps make advertising useful and delightful to our users, and valuable and results-driven for our advertisers and publishers.
The US base salary range for this full-time position is $150,000-$223,000 + 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 for new hire 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. 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, extract, and compile data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
  
• Shape new data-driven and privacy-preserving advertising and marketing products in collaboration with engineering, product, and customer-facing teams.
• Use causal inference methods to design and suggest experiments and new ways to establish causality, assess attribution, and answer strategic questions using data.