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 your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with 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. Forecast and set product team goals, design and evaluate experiments, monitor key product metrics, understand root causes of changes in metrics, build and analyze dashboards and reports, build key data sets to empower operational and exploratory analysis, and evaluate and define metrics. Propose what-to-build in the next roadmap, understand ecosystems, user behaviors, and long-term trends, identify new levers to help move key metrics, and build models of user behaviors for analysis or to power production systems. Influence product teams through the presentation of data-based recommendations, communicate state of business and experiment results to product teams, spread best practices to analytics and product teams, and lead cross-functionally on defining and executing on analyses, including across other data scientists, data engineers, software engineers, user researchers, among others. Work in Hadoop, Hive, MySQL, Oracle, and Vertica, and automate analyses and authoring pipelines via SQL and Python-based ETL frameworks.
Qualifications
Requires Master's degree (or foreign equivalent) in Statistics, Mathematics, Computer Science, Engineering, or a related field. Requires completion of a graduate-level course, research project, or internship in each of the following: Machine learning techniques Relational database (SQL or PL*SQL) Developing in Python Statistical analysis using R, SPSS, SAS, and Stata Quantitative analysis techniques: clustering, regression, pattern recognition, and descriptive and inferential statistics and Communicating and presenting results of data analyses