About the job
As a part of the Trust and Safety, Safe Browsing team, your role is driven by the mission to make the world’s information safely accessible to all, working alongside Safe Browsing Engineering to protect internet users across the globe from phishing, malware, and scams. As a part of this mission, you will support Safe Browsing systems that provide defenses against these threats for Google products such as Gmail, Chrome, Search, and Ads. As part of Trust and Safety, you will collaborate with anti-abuse teams across the company to identify and resolve the biggest problems that challenge the safety and integrity of our products.
Responsibilities
Create and evaluate AI agents that will help Safe Browsing classify web pages and reduce operational costs.
Perform data analyses to identify harmful entities, design and implement key performance metrics, examine trends, and identify system vulnerabilities.
Analyze potentially malicious websites to understand their behavior and impact on users, embracing technologies like LLMs to enhance our ability to fight abuse and phishing at scale.
Collaborate with, mentor, and provide guidance to global team members.
Review or manage exposure to sensitive or violative content as a core part of the role.
Qualifications
Minimum
Bachelor's degree or equivalent practical experience.
5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
Experience with SQL, Python, or other programming/scripting languages to manipulate datasets.
Preferred
Master’s or Ph.D. degree in a quantitative discipline (e.g. Computer Science, Statistics, Mathematics, Operations Research, etc.).
Experience with building AI agentic workflows or using different agentic architectures.
Experience in abuse and fraud disciplines, especially focused on web security, harmful content moderation, and threat analysis.
Knowledge in one or more of the following areas: statistical analysis and machine learning libraries (e.g., R, Tensor Flow), programming languages (e.g., Python), Large Language Models (LLMs), or generative AI.
Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.