Engineering Analyst, Trust and Safety Search

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.
  

Preferred qualifications:

• Master's degree in a quantitative discipline.
  
• 2 years of experience with one or more of the following languages: SQL, R, Python, or C++.
• 2 years of experience with machine learning systems.
• Excellent written and verbal communication skills.
  

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.

In this role, you will work to discover, measure, and mitigate user trust risks in Search through automated and scalable solutions. This would include working on Search results and various Search features. You will build relationships and work closely with Search engineers to protect Google Search users from spam and harmful content. You will identify and prevent manipulative behavior, contribute to the development and enforcement of spam guidelines, and partner with engineering teams to enhance search ranking algorithms. You will be exposed to graphic, controversial or upsetting content. Our aim is to resolve problems at scale by working with engineers on automated product protections, prompt-based large language model solutions, or through vendor support.

Responsibilities:

• Analyze and solve complex problems using data and statistical methods.
• Identify and prevent fraud and abuse.
  
• Improve tools and automated systems through data analysis, technical expertise, and present to stakeholders.