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.

Data Scientist, Analytics Responsibilities

• 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 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.

Minimum Qualifications

• Requires a bachelors degree in Business Administration with a statistical focus like Logistics and/or Business Technology, Logistics Management, Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Applied Sciences, or a related field. Requires 24 months of experience involving the following:


• 1. Features, design, and use-case scenarios across a big data ecosystem


• 2. Custom ETL design, implementation, and maintenance


• 3. Schema design and dimensional data modeling


• 4. Writing SQL statements


• 5. Analyzing data to identify deliverables, gaps, and inconsistencies


• 6. Managing and communicating data warehouse plans to internal clients and


• 7. Python.