Enforcement Detection Analyst, 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. 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

• Develop and implement strategies and solutions to enforce YouTube policies at scale. Provide data-driven insights and recommendations for effective abuse prevention and enforcement. Leverage Machine Learning, as appropriate.
• Collaborate closely with stakeholders and partners in engineering, product and policy to drive complex anti-abuse solutions involving and impacting various cross-functional areas.
• Provide rapid incident response for abuse problems, operating on their own. Analyze and draw conclusions on root-causes and define and implement mitigation steps.
• Learn complex and technical concepts and systems and deliver meaningful results using them. Communicate technical results and methods clearly.
• Design and refine prompts for LLMs to improve their accuracy in identifying and classifying abusive content and behavior. This may include prompt engineering, data labeling, and performance analysis.

Qualifications

Minimum qualifications:

• 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 managing projects and defining project scope, goals, and deliverables.
• Experience leveraging Large Language Models (LLMs) to automate the detection and mitigation of platform abuse, including spam, phishing, or violative content.

Preferred qualifications:

• Master's degree in a quantitative discipline.
• 2 years of experience with machine learning systems.
• Excellent problem-solving and investigative skills with the ability to go above and beyond to make operational improvements and solve tough problems.
• Excellent written and verbal communication skills.
• Proven track record of leveraging LLMs and generative AI technologies to solve business problems.