Develop, evaluate, and improve Google's advertising products including Search, Display, Apps, TV, and Video (e.g., YouTube).
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.).
- 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.
Responsibilities
- 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.
- Play a role in developing new ideas and methods that drive Ad measurement and generate business.
- Take on modern advertising’s tests and make an impact on the global ads ecosystem.
- Be trained in quantitative methodologies with knowledge of statistics and causal inference methods, and leverage data and technology to make business decisions.
- 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.
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
