Product Data Scientist, Sellside Ads

Build product analytics and modeling insights for sellside ad products by partnering across Ads teams and applying quantitative methods to large-scale auction data.

• Make data-driven decisions and prioritize stakeholder requests to maximize impact.
• Collaborate with a team of analysts and data scientists supporting PMs and engineering for sellside products including Ad Sense ,
  Google Ad Manager
  , and Ad Mob .
• Work cross-functionally with analyst colleagues in Finance and Publisher Intelligence
  .
• Lead ad-hoc deep dives into experiments and product performance.
• Provide quantitative support on auction fundamentals and engaged market dynamics
  .
• Support responses to regulatory inquiries and contribute quantitative analysis for published research on these topics.
• Identify, analyze, and communicate upcoming risks and opportunities for the business.
• Develop and scale infrastructure that supports existing analyses.
• Present findings to decision-makers and executives across the company.

• Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems).
• Experience coding for analysis, including Python
  , R, or SQL
  .
• Equivalent path: 2 years of experience with a Master’s degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

• Python
• R
• SQL
• Gemini

• Salary: USD 138, per year
• Bonus: 15% target
• Equity
• Benefits
• Health insurance

• Product analysts and data scientists collaborate within and across Ads product area groups (PAGs) on complex, data-intensive problems.
• Deliver product analytics
  , in-depth analyses,
  modeling
  , dashboards
  , metrics definitions
  , and analytics consulting
  .
• Interpret and analyze huge data sets generated from real-time ads auctions running at 5-10M QPS (queries per second).
• Study longitudinal issues such as engagement and customer loyalty
  , new business segments, competitive positioning, and risks.
• Support strategic Ads product decisions with a data-driven and objective perspective, producing insights and recommendations.
• Leverage AI innovation, including cutting‑edge machine learning and Generative AI models like Gemini
  , to power a multi‑billion dollar global business.
• Work impacts billions of users by helping protect users from harm, improving ad quality, and optimizing campaigns for advertiser return‑on‑investment.
• Collaborate closely with teams including Google Research and Deep Mind
  .

Location: New York, NY (onsite)