Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.
Responsibilities
Collect, organize, interpret, and summarize statistical data in order to contribute to the continued growth of Meta's infrastructure. Apply experience in quantitative analysis and data mining to improve, optimize, and expand Meta’s infrastructure across a variety of domains with an emphasis on long-term and strategic initiatives. Work cross-functionally as a strategic partner to define priorities and develop project roadmaps in synergy with partner teams. Build consensus and earn commitment from partners. Drive execution through fast iteration. Ensure coordination of projects across related workflows to maximize impact and avoid duplication and overlaps. Drive efficient data exploration and modeling. Build pragmatic, scalable, and statistically rigorous solutions to large-scale web, mobile and data infrastructure problems by leveraging or developing statistical and machine learning methodologies. Generalize methodologies for broader application within and outside domain. Work on problems of moderate scope where analysis of situations or data requires a review of a variety of factors. Exercise judgment within defined procedures and practices to determine appropriate action.
Qualifications
Requires a Master's degree (or foreign degree equivalent) in Data Science, Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Applied Sciences, or a related field Requires completion of a graduate-level course, research project, or internship involving the following: Performing quantitative analysis including data mining on highly complex data sets Data querying language(s) including SQL Scripting language(s) including one of the following: Python, PHP, or JavaScript Statistical or mathematical software including one of the following: R, SAS, or Matlab Applied statistics or experimentation, such as A/B testing, in an industry setting Machine learning techniques ETL (Extract, Transform, Load) processes and Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics