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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.
Job Responsibility:
Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of Meta products
Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products
Partner with Product and Engineering teams to solve problems and identify trends and opportunities
Inform, influence, support, and execute our product decisions and product launches
May be assigned projects in various areas including, but not limited to, product operations, exploratory analysis, product influence, and data infrastructure
Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors
Demonstrate good judgment in selecting methods and techniques for obtaining solutions
Requirements:
Master's degree (or foreign equivalent) in Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences, or a related field and three years of work experience in the job offered or in a computer-related occupation
Requires three years of experience in: Performing quantitative analysis including data mining on highly complex data sets
Data querying language: SQL
Scripting language: Python
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
Relational databases
Large-scale data processing infrastructures using distributed systems
Quantitative analysis techniques, including one of the following: clustering, regression, pattern recognition, or descriptive and inferential statistics