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In office (Mountain View)
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Senior · 7+ years exp
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Confirmed on the employer's own hiring board on Nov 7, 2026. First seen by Alion on Nov 5, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

Maps Anti-Scraping Protection team is dedicated to protecting Google's valuable Geo data assets from automated exfiltration. The core mission is to protect Maps data and map details from programmatic exfiltration.

A core priority is to ensure minimal friction for the legitimate users. The work is crucial for maintaining the integrity of Google Maps, user trust, and Geo's competitive edge. This is approached through identifying, analyzing, and mitigating various forms of abuse across all Maps surfaces, leveraging both established techniques and cutting-edge research.

In this role, you will understand the evolving bot and scraper landscape, identify new abuse and inorganic traffic patterns targeting Geo data and services, and measure the effectiveness of our protections and suggest improvements. 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 AI/ML.

****Use this template only when existing Area Templates don't apply. For one-off use cases, not ongoing roles. If you need to create a NEW template for your team submit a request at go/jdreview.****

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.

Responsibilities

  • Investigate and analyze complex patterns of data exfiltration and abuse on Google Maps, utilizing data-driven insights to develop and propose effective countermeasures. Analyze large-scale logs data from various Geo surfaces to identify, understand, and monitor inorganic traffic, scraping activities, and abuse patterns.
  • Design, test, and launch new anti-scraping rules, models, and system enhancements tailored to Geo's products and infrastructure. Evaluate the effectiveness of detection mechanisms, understand the impact on both scrapers and legitimate user experience.
  • Develop metrics to measure scraper impact on Geo services and the effectiveness of anti-scraping defenses. Contribute to the development of signals and features for ML models to detect scraping attempts.
  • Investigate proof-of-concept attacks and research reports that identify blind spots and guide the team's development priorities.
  • Develop threat intelligence on actors, motivations, tactics, and the ecosystem targeting Geo data.

Qualifications

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 7 years of experience in managing projects and defining project scope, goals and deliverables.
  • 7 years of experience in a data-intensive role such as threat intelligence, data science, trust and safety, or fraud analysis.
  • 7 years of experience in data analysis including identifying trends, generating summary statistics and drawing insights from quantitative and qualitative data.
  • Experience with threat intelligence, anti-abuse, security, network analysis, or fraud detection.

Preferred qualifications:

  • Master's degree in Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field.
  • Experience with abuse detection, spam, web development or project management.
  • Experience with data analysis, statistical analysis and data science and large language models.
  • Experience with Search Engine Optimization (SEO).

  • Experience in coding with SQL, JavaScript, Python, or C++.
  • Understanding of machine learning systems and concepts.
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