Senior Engineering Analyst

Minimum qualifications:

• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering) or equivalent practical experience.
• 5 years of experience in a Trust and Safety, anti-abuse, security engineering, or data analysis role.
• Experience constructing SQL queries and utilizing data extraction techniques to analyze datasets.
• Experience designing, testing, and implementing technical solutions, workflows.
• Experience working with AI/LLM technologies or Machine Learning models.

Preferred qualifications:

• Understanding of software engineering and automation principles, with experience in a data-focused scripting language (e.g., Python, C++, or R).
• Ability to collaborate with a variety of stakeholders ranging from policy to engineering teams to gather technical requirements, explain model architectures, and iterate on system improvements.
• Exceptional communication skills, along with the ability to synthesize complex analytical projects into actionable product insights for cross-functional or executive audiences.
• Proficiency in data visualization and statistical analysis techniques to map abuse journeys and evaluate system performance.

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.

As a Senior Engineering Analyst for the YouTube Monetization, you are an independent, critical thinker with sound judgment who has a bias towards action, passion for Internet policy and legal issues and a penchant for defining consistent and scalable standards, especially in areas that are ambiguous or still evolving. You will act as a proven domain expert to solve complex monetization quality challenges. You will drive technical projects that preserve the YouTube advertising ecosystem by balancing creator opportunities with robust advertiser brand safety. Leveraging data analysis, machine learning models, and Generative AI, you will design, test, and implement scalable enforcement workflows from scratch. You will collaborate cross-functionally with Engineering, Product, and Trust and Safety partners to align on technical direction and co-develop product protections. Managing project priorities, adjacent timelines, and technical resources, you will proactively identify emerging risks, optimize existing protections, and advocate the team's AI-first transformation. Your strategic insights and rigorous analysis will directly influence long-term product decisions, reducing user harm and driving efficiencies across YouTube Monetization.

Responsibilities

• Design, implement, and optimize scalable enforcement workflows, models, and technical solutions from scratch to protect the YouTube monetization ecosystem.
• Co-develop product protections and integrate Generative AI/Large Language Models (LLMs) technologies (e.g., machine-readable policies, AI agents) with partner engineers.
• Write complex, efficient SQL and Python code independently to extract and analyze high-volume product metadata and compute classifier performance metrics.
• Perform complex anti-abuse investigations and deep-dive data analyses to identify system gaps, discover novel threat vectors, and implement robust mitigations. Review controversial or offensive content to validate and improve the precision and recall of Applied AI and automated protection systems.
• Translate complex, nuanced technical concepts and data insights into recommendations to influence leadership and cross-functional strategies. Drive outcomes for multiple adjacent technical projects, managing priorities, resource allocation, and project timelines across quarters.