Shape and support privacy-preserving, data-motivated advertising products by collaborating with engineering, product, and customer-facing teams. Define key advertising questions (e.g., incrementality, privacy impact, user behavior) with multiple teams then develop and implement quantitative solutions. Develop, evaluate, and improve Google's advertising products including Search, Display, Apps, TV, and Video (e.g., YouTube). Develop new science and translate it into deployed products. Develop new ideas and methods that drive Ad measurement and generate business. Build and drive impact on ad-systems both at Google and in the Advertising Technology and Marketing Technology industry. Take on modern advertising’s tests and make an impact on the global ads ecosystem.
Requirements
- coding (e.g., Python, R, SQL)
- querying databases or statistical analysis
- Experience with Deep Learning.
- Experience in working on applied data problems in Ads (e.g., bidding, ranking, etc.).
- quantitative methodologies with knowledge of statistics and causal inference methods
- leverage data and technology to make business decisions.
Responsibilities
- Shape and support privacy-preserving, data-motivated advertising products by collaborating with engineering, product, and customer-facing teams.
- Define key advertising questions (e.g., incrementality, privacy impact, user behavior) with multiple teams then develop and implement quantitative solutions.
- Design experiments and establish causality using causal inference to assess attribution and answer data-motivated questions.
- Analyze datasets to solve testing problems and conduct analysis from data gathering and exploration to model development and present results to stakeholders.
- Build analysis pipelines for insights, develop an understanding of Google's data structures, advocating for necessary improvements.
- Develop, evaluate, and improve Google's advertising products including Search, Display, Apps, TV, and Video (e.g., YouTube).
- Collaborate with a multi-disciplinary team of engineers, analysts, and product managers to develop new science and translate it into deployed products.
Other
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
- 3 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.
- Master's degree or PhD in Statistics or a related field.
- 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD.
- Mountain View, CA, USA; New York, NY, USA
