US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Investigate and analyze patterns of abuse on Google Search, utilizing data-motivated insights to develop countermeasures and enhance platform security, and analyze datasets to identify trends, patterns, and anomalies that may indicate abuse within Google Search.
- Develop and track 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.
- Review proof-of-concept attacks and research reports that identify blind spots and guide the engineering team's development priorities, 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.
Minimum qualifications:
- 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.
Preferred qualifications:
- Master's degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, 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.