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
Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how users interact with both consumer and business products. Identify the opportunities most important for growth to remove barriers for product adoption, retention, engagement, and/or monetization. Partner with growthfocused engineering teams to execute on projects based on factors identified to accelerate the growth and adoption of Facebook’s products. Understand funnels, ecosystems, user behaviors, and long-term trends in the adoption of Facebook’s products to identify opportunities for step-changes and angle changes in growth. Define and analyze metrics that inform the success of products. Communicate the state of business, experiment results, and opportunities to product teams. Influence and inform product teams through presentation of data-based recommendations.
Qualifications
Requires Bachelor’s degree (or foreign equivalent) in Business Analytics, Statistics, Economics, Mathematics, Mathematical Economics, Engineering, or related field, and one year of work experience in job offered or in a data analytics-related occupation Experience must include one year of experience in the following: Quantitative analysis Working collaboratively with product teams, such as product management, engineering, design, data science, or data engineering Manipulating data sets through statistical software (R, SAS, or Pivot Tables) Funnel/website optimization or outbound communication channels like email or push notifications SQL Product optimization or growth best practices Making analytical, data-driven decisions and communicating the results of analyses and Statistics, including hypothesis testing, product experimentation, regressions, and experimentation logic and biases