Senior Data Scientist, Product, Ads Privacy and Regulations
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Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- Knowledge of financial forecasting, scenario analysis and risk assessment for Ads.
- Familiarity with global privacy regulations (e.g., General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Digital Markets Act (DMA)) and their implications relevant to technology companies.
About the job
The Ads Privacy and Safety team is dedicated to fostering trust and transparency within the Google Ads ecosystem. This involves ensuring safety and respect for users, advertisers, and publishers by combating invalid traffic, promoting privacy-respecting business generation practices that empower user control, and advancing content understanding through human and machine intelligence.
Responsibilities
- Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Help solve problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems to reach an optimal solution.
- Build new processes, procedures, methods, tests, and components with foresight to anticipate and address future issues.
- Report on Key Performance Indicators (KPIs) to support business reviews with the cross-functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
- Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.
- Influence across teams to align resources and direction.
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