Integrity Analyst, Anti-Scraping

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities â€" we're just getting started.

Are you interested in solving complex problems that are geared towards improving the privacy of people using Facebook's family of apps? Are you excited about learning how to scale and automate processes? Come join us at Facebook! The Anti-Scraping team uses state of the art real-time and modeling systems to prevent abuse. We are building an analytics-driven team that thinks upstream to constantly implement solutions at scale through better automation strategies. Our focus on data analysis, machine learning, and a robust infrastructure of back-end systems allows us to work effectively with our engineering, operations and product teams who build proprietary tools and techniques to enforce the quality of content at scale. Successful candidates for this team have a bias toward action and enjoy finding patterns amid chaos, making quick decisions, and aren't afraid of being wrong. The ideal candidate will have a background in a quantitative or technical field, will have experience working with large data sets, and will have in-depth experience in data-driven decision making. You are scrappy, focused on results, a self-starter, and have demonstrated success in using analytics to reduce abuse and negative user experiences across the platform. This position is located in our Menlo Park office.


  • Apply your knowledge in quantitative business analysis, data mining, and the presentation of data to identify trends and opportunities in detecting and blocking scraping
  • Analyze and interpret data on which to devise hypotheses
  • Implement effective countermeasures to stop scraping based on these identified patterns
  • Requires contributing to Facebook’s anti-abuse codebase in PHP, Python, and Haskell
  • Be a thought leader for data-informed initiatives and guide the team’s overall direction
  • Partner with Data Science, Product, Engineering, and Operations teams to solve problems at scale
  • Work effectively with our partners in Legal and eCrime to investigate scrapers and scraping activities
  • Work with product teams to deeply understand their product features, use cases, and measure scraping
  • Work with internal teams to understand what happens with exfiltrated data
  • Partner with internal teams to help shape and inform bot detection technology
  • 2+ years experience doing quantitative analysis
  • Experience in functional or scripting language (JavaScript, PHP, Python, OCaml, etc.)
  • BA/BS in Computer Science, Math/Finance, Physics, Applied Economics, Statistics or other technical field
  • Experience in adversarial space like fraud or spam
  • Experience querying large data sets and SQL

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