Engineering Analyst, Anti-scraper, Search
@ Google

Mountain View, CA
$200,000
On Site
Full Time
Posted 8 hours ago

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Job Details

Overview

Google is seeking an Engineering Analyst, Anti-scraper, Search, responsible for investigating abuse patterns and developing countermeasures in Google Search. You will work with large datasets, perform data analysis and statistical evaluations, design systems enhancements, and develop metrics for anti-scraping defenses.

Minimum Qualifications

  • Bachelor's degree or equivalent practical experience
  • 7 years of data analysis experience
  • 7 years of project management experience
  • Expertise in data and statistical analysis

Preferred Qualifications

  • Master's degree in quantitative field
  • 10 years in data roles such as threat intelligence or fraud analysis
  • Experience with SQL, JavaScript, Python, or C++
  • Background in machine learning and abuse detection

Responsibilities

  • Investigate and analyze patterns of abuse on Google Search
  • Develop metrics and track anti-scraping measures
  • Collaborate with engineering teams on system enhancements
  • Research proof-of-concept attacks and detection inefficiencies
  • Develop machine learning signals for detecting abusive behavior
  • Maintain threat intelligence on scraper activities

Key skills/competency

  • data analysis
  • machine learning
  • threat intelligence
  • fraud detection
  • SQL
  • JavaScript
  • Python
  • abuse detection
  • project management
  • countermeasures
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How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Highlight relevant data and project management skills.
  • Research Google: Understand their products and engineering challenges.
  • Prepare your portfolio: Showcase past data analysis and threat projects.
  • Practice technical questions: Review SQL, Python, and statistical methods.

📝 Interview Preparation Advice

Technical Preparation

Review data analysis and SQL fundamentals.
Practice Python and JavaScript coding exercises.
Study machine learning model signals.
Analyze trend patterns in sample datasets.

Behavioral Questions

Describe a challenging project management experience.
Explain a complex data analysis task.
Share a team collaboration example.
Discuss handling unexpected technical issues.

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