Data Scientist Manager, Fraud

    • Tel Aviv, Israel

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.

For many people around the world, basic financial services are still out of reach: about 1.7 billion adults globally remain unbanked. The cost of that exclusion is significant - $25 billion is lost by migrants every year through remittance fees. This is the challenge we're hoping to address with Novi, a Facebook subsidiary whose goal is to provide people everywhere access to safe and affordable financial services through through the Libra payment system, which is built on blockchain technology. Our first product will be a digital wallet - Novi - for the Libra network, and it will be available in Messenger, WhatsApp, and as a standalone app.

We're looking for a data science manager to join our fraud prevention team and help play an active role in protecting our community. We prevent fraud by using advanced detection tools that scan billions of data points to identify signs of activities that violate our policies. As a manager, you will lead a team of fraud data scientists responsible for analyzing data to generate insights about fraud patterns and developing decision policies to prevent them. Your team will also be responsible for building the high-level view of the ecosystem to determine where we should focus and what are the new detection / ML capabilities we should develop.

You will enjoy leading a team of people working with one of the richest data sets in the world, cutting-edge technology, and the ability to see your insights turned into real products on a regular basis. You will make a real and meaningful impact on the world. The perfect candidate will have a background in a quantitative or technical field as well as experience leading teams analyzing data at scale in the fraud domain. This position is located in our Tel Aviv office.

  • Lead a team of data scientists responsible for designing, implementing and managing fraud prevention efforts. The team will determine the types of fraud to be managed and utilize -Facebook's- rich data sets to build real time detection and decisioning capabilities.
  • Support the growth and development of team members.
  • Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand fraud and how to prevent it.
  • Define and monitor key metrics. Understand changes in key metrics and lead change where needed.
  • Partner with Product and Engineering teams to build experiences that will support fraud prevention efforts.
  • Communicate the state of business, experiment results and recommendations to a cross-functional team and leadership.
  • 2+ years of experience in managing other team members in a formal capacity
  • 4+ years of experience doing quantitative analysis
  • 2+ years of experience in an analytical role in a technology company, consulting, investment banking, or product management
  • Experience in SQL or other programming languages.
  • Experience working in a machine learning heavy environment
  • Ability to initiate and drive projects to completion with minimal guidance
  • Ability to communicate the results of analysis
  • Bachelor Degree in Computer Science, Math, Physics, Engineering, or related quantitative field.
  • Understanding of statistical analysis
  • Experience with large data sets and distributed computing (Hive/Hadoop)

Back to top