Senior Engineering Traffic Analyst, Search, Anti-scraper

Google•Zurich, CA

2h•$159,000 - $230,000

About The Position

As a traffic integrity analyst, you will help protect Google Search by analyzing the evolving bot and scraper landscape, identifying abuse and inorganic traffic patterns, measuring the effectiveness of protections, and recommending improvements. You will work closely with software engineers, data scientists, and site reliability engineers to develop, deploy, and refine countermeasures. The role involves identifying abuse trends, tracking threat actors, and assessing how protections affect both bots and real users through extensive data analysis and ML/AI.

Requirements

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.
5 years of experience managing projects and defining project scope, goals, and deliverables.
Experience with statistical analysis, data science, and data analysis.

Nice To Haves

Master's degree in a quantitative field such as Statistics, Computer Science, Mathematics, or Engineering.
5 years of experience in a data-intensive role such as threat intelligence, data science, trust and safety, or fraud analysis.
Experience with threat intelligence, anti-abuse, security, network analysis, fraud detection, and Search Engine Optimization (SEO).
Experience with SQL, JavaScript, Python, or C++.
Experience with machine learning systems and concepts.
Experience in data analysis, data science, statistical analysis, abuse detection, spam, web development, project management, and fraud detection.

Responsibilities

Investigate and analyze patterns of abuse on Google Search, using data-driven insights to develop countermeasures and enhance platform security; analyze datasets to identify trends, patterns, and anomalies that may indicate abuse.
Develop and track metrics to measure scraper impact and the effectiveness of anti-scraping defenses; collaborate with engineering teams to design, test, and launch anti-scraper rules, models, and system enhancements.
Review proof-of-concept attacks and research reports to identify blind spots and guide engineering priorities; evaluate detection mechanisms and understand their impact on scrapers and real users.
Contribute to the development of signals and features for machine learning models that detect abusive behavior.
Develop and maintain threat intelligence on scraper actors, their motivations and tactics, and the scraper ecosystem.