About the job

Ads Metrics is the DS team for Search, Owned and Operated (O&O) ads. We support the Search Ads and Google Experience (SAGE) organisation in developing the most important ad products at Google from classic text ads, to rich shopping ads, to exciting new products like Demand generative Campaigns, Local Ads, Travel Ads, etc. These products are at the heart of Google’s business and are advanced, and they are rapidly growing and evolving. We guide product development and executive decisions with data. Particularly, we measure the long-term impact of all the changes we make on users, advertisers, and Google systems with experiment designs; identify new growth opportunities with data analysis; and understand the trade-offs between user, advertiser and Google value with principled frameworks. We work closely with our Engineer/PM collaborators to improve our products, and with SAGE executives to understand the growth levers and their impact on business. Our role is to drive long-term value for Google’s business with insightful data science.

In this role, you will be role model and professional coach for data scientists and will help in setting clear expectations, openly evaluating performance, upholding accountability, and providing issues (within and outside their team) to stretch their skills.

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 $248,000-$349,000 + 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

• Lead Ads Metrics team to explore the generative AI exploration. There are a lot of interesting projects to consider, particularly on the AI mode surface. Evaluate experiments to see what works vs. not, assess how to best serve embedded ads, understand users’ commercial journey on the surface, and develop strategy for business generation.

• Demonstrate communication with ads product/engineer/executives, and other organizations (customer solutions, business, etc.) to understand their needs, assist in decision making, and align on solutions.

• Be responsible for a high level of productivity.

• Understand and model the importance of rigorous analysis, knowing that it will look different in these nascent businesses.

Minimum qualifications

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

• 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

Preferred qualifications

• 12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.

• 6 years of experience as a people manager within a technical leadership role.

• 6 years of work experience in stats analysis, strategy analysis, or AI in tech companies.

• Excellent data intuition and great business acumen.