Intro
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.
Summary
Business Payments handles the $70 Billion plus payments advertisers make to Facebook. Our mission is to make this as seamless a process as possible, while giving our customers the tools and products they need to run and grow their business. As Facebook doubles down on payments with the creation of the F2 organization, business payments is positioned to unlock billions of dollars in new spend by refining existing systems, deciding what billing system is best for each of our 7 Million plus customers, and creating new revenue verticals. We are looking for strong Data Scientist who can work closely with Engineering, Product, Design, and Research leads to drive analytics, modeling, and product strategy that make company level impact. Ideal candidates will have genuine interest in diving deep into the data to develop a theory and weave a compelling and digestible narrative.
Required Skills
- Build a long term vision with an understanding of the competitive landscape
- Understand the complex payments engine and identify the bottlenecks and opportunities
- Identify low-hanging fruit and develop best-in-class analytical solutions
- Build an experiment design and evaluation framework customized to the nuances of the product area
- Identify and build the right metrics for measuring success and failure
- Develop scalable decisioning systems ready for production environments
- Drive data engineering priorities that enable analytical and modeling success
- Level-up the analytics organization with deep domain expertise
- Drive stakeholder and executive trust with strong communication founded on technical rigor
