Spam Analyst

(Menlo Park, CA)

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 — we're just getting started.

Passionate about diving into the world of big data and trends analyses? Interested in solving complex problems that are geared towards improving Facebook and its community's experiences? Excited about learning how to scale and automate processes? Come join Site Integrity at Facebook! The Site Integrity teams uses a state of the art Haskell-based system to prevent spam and abuse from impacting Facebook. 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 to 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 perfect 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.

Responsibilities

  • Apply your expertise in quantitative business analysis, data mining, and the presentation of data to identify trends and opportunities in driving down spam and other nefarious behavior
  • Analyze and interpret data in order to devise hypotheses on how spam and other nefarious activity is proliferating
  • Implement effective countermeasures to eliminate spam based on these identified patterns
  • Requires contributing to Facebook's anti-abuse codebase in Haskell.
  • Be a thought leader for data-informed initiatives and guide the team's direction overall
  • Partner with Data Science, Product, Engineering and Operations teams to solve problems at scale

Minimum Qualifications

  • 4+ years experience doing quantitative analysis.
  • Experience in functional or scripting language (JavaScript, PHP, Python, OCaml)

Preferred Qualifications

  • BA/BS in Computer Science, Math/Finance, Physics, Applied Economics, Statistics or other technical field. Advanced degrees.
  • Experience in adversarial space like fraud and spam.
  • Experience with data sets and familiarity with SQL.
  • Development experience in Haskell.

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