senior Data Scientist hybrid · Posted Mar 10, 2026
$240,000 – $334,000
USD per year
Skills
Python R SQL
AI Summary
Senior-level Data Scientist driving measurement and analytics strategy for Google Ads. Owns end-to-end analytical projects using SQL, R, Python to guide advertising strategy, manage stakeholder relationships, and lead cross-functional teams toward actionable insights on advertiser ROI and inventory efficiency.

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 the advertising solutions effectively connect businesses with customers and deliver measurable results across the various Ad platforms.

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

In this role, you will help drive the goal of how large advertisers buy Google and third-party advertising inventory efficiently. You will be responsible for setting the team's strategic direction, and 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 $240,000-$334,000 + 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). Direct projects that combine analytical and organizational complexity towards clear, sound, and actionable decisions.
  • Own projects end-to-end, covering problem definition, metrics development, data extraction, manipulation, visualization, creation, and implementation of analytical/statistical models, and presentation to stakeholders.
  • Oversee the integration of cross-functional and cross-organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
  • Provide direction and accomplish results through leading/impacting the contributions of others.
  • Build an understanding of the data sets used by Enterprise Platforms and partner teams, collaborate with Engineering teams to identify and address instrumentation gaps, ensure accurate data collection for key functionalities, with a focus on the most impactful features.

Minimum qualifications:

  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 13 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience with a Master's degree).
  • 5 years of experience as a people manager within a technical leadership role.

Preferred qualifications:

  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 15 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
  • 6 years of experience as a people manager within a technical leadership role.
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