About the job

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

Measurement is a cornerstone of performance advertising, driving the majority of Google Ads business growth. Accurate and unbiased measurement empowers bidding engines to maximize advertiser ROI, fostering growth for both advertisers and Google. The Product Analyst team applies advanced analytics to guide Google Ads strategy in this crucial area, ensuring that our advertising solutions effectively connect businesses with customers and deliver measurable results across our ad platforms.

The AIM Data Science team provides quantitative support, market understanding, and a strategic perspective to our partners throughout the organization in close collaboration with the Ads and Commerce Finance team.

As the Staff Product Data Scientist for Enterprise Platforms, you will help drive the vision of how large advertisers buy Google and third-party advertising inventory efficiently. You will be responsible for setting the team's strategic direction, managing stakeholder relationships.

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 $183,000-$271,000 + 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

• Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide analytical thought leadership through proactive and strategic contributions (e.g., suggest new analyses, infrastructure, or experiments to drive improvements in the business).

• Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders.

• Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing them, generating hypotheses, and making recommendations from a perspective that combines both analytical and product-specific expertise.

• Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.

• Directly or indirectly oversee the contributions of others and develop colleagues’ capabilities in the area of specialization.

Minimum qualifications

• 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 (e.g., Python, R, SQL), or 8 years of work experience and a Master's degree.

Preferred qualifications

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

• 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).