Requirements

Bachelor's degree or equivalent practical experience.
2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
2 years of experience with SQL.

Nice to haves

Experience in data management, metrics analysis, experiment design, and automation.
Experience with classification systems, ranking systems, or similar.
Experience collecting, managing, and synthesizing data sets and information from disparate sources, statistical modeling, data mining, and data analysis.
Experience in problem-solving with a quantitative mind, capable of translating insights into business strategies and actions.
Understanding of high-level product and policy knowledge with the ability to design training roadmaps and communicate and persuade between multiple levels.

Perform analysis and investigations using a variety of data sources and take enforcement actions to identify and defend novel fraud and abuse on Google's ad products.
Partner with Engineering teams to improve ad traffic infrastructure, defense systems, and workflows by proactively identifying and implementing efficiency improvements through advanced machine learning techniques, scaled defenses, and automation.
Drive full life-cycle projects across Product, Engineering, and Trust and Safety teams to prevent abuse by improving policies and closing product vulnerabilities.
Work collaboratively with teammates around the globe and deliver projects from beginning to end in a timely manner.
Review or be exposed to sensitive content.

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