Investigate and analyze patterns of abuse on Google Search, utilizing data-driven insights to develop counter measures and enhance platform security.
Requirements
- Experience with threat intelligence, anti-abuse, security, network analysis, fraud detection, Search Engine Optimization (SEO).
- Experience with machine learning systems and concepts.
- Experience in Abuse Detection, Spam, Web Development, Project Management, Fraud Detection, Data Analysis, Data Science, Statistical Analysis.
- Proficiency in SQL, JavaScript, Python, or C++.
- 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
- 3 years of experience in a data-intensive role such as threat intelligence, data science, trust and safety, or fraud analysis.
Responsibilities
- Investigate and analyze patterns of abuse on Google Search, utilizing data-driven insights to develop counter measures and enhance platform security and analyze large datasets to identify trends, patterns, and anomalies that may indicate abuse within Google Search.
- Develop key metrics to measure scraper impact and the effectiveness of anti-scraping defenses and collaborate with engineering teams to design, test, and launch new anti-scraper rules, models, and system enhancements.
- Investigate proof-of-concept attacks and research reports that identify blind spots and guide the engineering team's development priorities and evaluate the effectiveness of existing and proposed detection mechanisms, understanding the impact on both scrapers and real users.
- Contribute to the development of signals and features for machine learning models to detect abusive behavior and develop and maintain threat intelligence on scraper actors, motivations, tactics and the scraper ecosystem.
Other
- Bachelor's degree or equivalent practical experience.
- 2 years of experience managing projects and defining project scope, goals, and deliverables.
- Master's degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Engineering).
