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 Responsibilities

• Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.


• Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.


• Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.


• Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.


• Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.


• Telecommuting is permitted from anywhere in the United States.

Minimum Qualifications

• Requires a Master's degree in Mathematics, Statistics, Analytics, Engineering, or a related field and 36 months of experience in the job offered or in a related occupation. Experience must include 36 months involving the following:


• 1. Machine learning techniques


• 2. Working with large data sets and network-based data including TCP or HTTP


• 3. ETL (Extract, Transform, Load) processes


• 4. Relational databases including (SQL or PL*SQL


• 5. Python or R


• 6. Quantitative analysis techniques including clustering, regression, or pattern recognition


• 7. Quantitative analysis techniques including descriptive and inferential statistics


• 8. Communicating and presenting results of data analyses.