Business Data Scientist, YouTube Trust and Safety

About the Job

Fast-paced, dynamic, and proactive, YouTube’s Trust & Safety team is dedicated to making YouTube a safe place for users, viewers, and content creators around the world to create, and express themselves. Whether understanding and solving their online content concerns, navigating within global legal frameworks, or writing and enforcing worldwide policy, the Trust & Safety team is on the frontlines of enhancing the YouTube experience, building internet safety, and protecting free speech in our ever-evolving digital world.

The Quality Analytics team operates in a critical environment, providing comprehensive analytics for Channel enforcements that rely on complex tooling and hybrid human-AI review systems. We manage a consistent schedule of executive reporting, where frequent and significant policy changes directly impact System Level Precision (SLP), Root Cause Analysis (RCA) loops, and core creator experience metrics (such as appeals and reinstates). As the demand for sophisticated insights continues to accelerate, this role is critical in navigating this increasing complexity, assessing quality-vs-cost trade-offs, and driving decision-making across our extended workforce and detection pipelines.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

Responsibilities

• Maintain and improve quality metrics and risk profiling frameworks for Channel enforcements, ensuring consistency in reporting and socialization across stakeholders.
• Manage and drive RCA processes for both human and automated actions, identifying trends in new abuse vectors that fall outside standard Trust & Safety (TnS) policies. Design and implement label-based quality experiments for detection enablement; perform estimation of Precision/Recall and summarize findings to inform policy and detection strategy.
• Monitor the quality-vs-cost trade off between various workforce tiers, providing data-driven recommendations for resource allocation.
• Build and maintain automated data pipelines and reporting dashboards that provide vendor-level and agent-level insights to Global Vendor Operations (GVO) for performance management.
• Partner with YouTube Data Science, Scaled Abuse, and GVO teams to support the launch of metrics infrastructure and resolve technical issues.

Qualifications

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
  

Preferred qualifications:

• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• 3 years of experience in data analysis, data science, or a related quantitative role.
• Experience in SQL for data extraction, transformation, and analysis.