Data Scientist

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

• 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.

Minimum Qualifications

• 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 and
• Leading data-driven projects from definition to execution, including defining metrics, experiment, design, communicating actionable insights