From Google's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
As a Traffic Integrity Analyst, you will be at the forefront of protecting Google Search.
As a Traffic Integrity Analyst, you will be at the forefront of protecting Google Search. You'll use your problem solving skills to understand the evolving bot and scraper landscape, identify new abuse and inorganic traffic patterns, and measure the effectiveness of our protections and suggest improvements. You will collaborate closely with Software Engineers, Data Scientists, and Site Reliability Engineers to develop, deploy, and refine countermeasures. You will identify abuse trends, track threat actors and measure the effectiveness of our protections against bots, as well as impact on real users through extensive data analysis and ML/AI.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $188000 - $274000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Investigate and analyze patterns of abuse on Google Search, utilizing data-motivated insights to develop countermeasures and enhance platform security. 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. 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. Evaluate the effectiveness of existing and proposed detection mechanisms, understanding the impact on scrapers and real users.
Contribute to the development of signals and features for machine learning models to detect abusive behavior. Develop and maintain threat intelligence on scraper actors, motivations, tactics and the scraper ecosystem.
Bachelor's degree or equivalent practical experience.
7 years of experience in data analysis including identifying trends, generating summary statistics and drawing insights from quantitative and qualitative data.
7 years of experience in managing projects and defining project scope, goals and deliverables.
Experience with data analysis, statistical analysis and data science.
Master's degree in Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field.
10 years of experience in a data-related role such as threat intelligence, data science, trust and safety, or fraud analysis.
Experience with threat intelligence, anti-abuse, security, network analysis, fraud detection or Search Engine Optimization (SEO).
Experience with SQL, JavaScript, Python or C++.
Experience with machine learning systems and concepts.
Experience with abuse detection, spam, web development or project management.
Bachelor's degree or equivalent practical experience.
7 years of experience in data analysis including identifying trends, generating summary statistics and drawing insights from quantitative and qualitative data.
7 years of experience in managing projects and defining project scope, goals and deliverables.
Experience with data analysis, statistical analysis and data science.
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