This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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:
Utilize advanced knowledge of operations research, management science, data mining, mathematics, Hadoop/Hive, SQL, Excel, and MicroStrategy to drive efficient analytics and reporting
Identify actionable insights, suggest recommendations and influence the direction of Online Operations by effectively communicating results to cross functional groups, including Online Ops leadership
Leverage data and mathematical principles to provide insights about user behavior, inform business decisions, and solve large scale data infrastructure problems
Work cross functionally to define problem statements, collect data, build analytical models and make recommendations
Develop mathematical models and perform data analysis to drive insights to improve Meta's operations
Partner with Product and Engineering teams to solve problems and identify trends and opportunities
Build and analyze dashboards, reports and key data sets to empower operations and exploratory analysis
Requirements:
Master's degree (or foreign equivalent) in Mathematics, Statistics or related field
Requires completion of a graduate-level course, research project or internship involving the following: Analytics
Data querying languages such as SQL
Scripting languages such as Python
Statistical mathematical software such as R
Solving analytical problems using quantitative approaches
Understanding ecosystems, user behaviors & long-term product trends
Leading data-driven projects from definition to execution, including defining metrics, experiment, design, communicating actionable insights