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, WhatsApp, and Novi 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 ResponsibilitiesApply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business productsPartner with Product and Engineering teams to solve problems and identify trends and opportunitiesInform, influence, support, and execute our product decisions and product launchesForecast and set product team goalsDesign and evaluate experimentsMonitor key product metrics, and understand root causes of changes in metricsBuild and analyze dashboards and reportsBuild key data sets to empower operational and exploratory analysisEvaluate and define metricsPropose what to build in the next roadmapUnderstand ecosystems, user behaviors, and long-term trendsIdentify new levers to help move key metricsBuild models of user behaviors for analysis or to power production systemsInfluence product teams through presentation of data-based recommendationsCommunicate state of business, experiment results, etc. to product teamsSpread best practices to analytics and product teamsWork in Hadoop and Hive primarily, sometimes MySQL, Oracle, and VerticaAutomate analyses and author pipelines via SQL and Python-based ETL frameworkTelecommuting is permitted from anywhere in the United StatesMinimum QualificationsPhD in Statistics, Mathematics, Economics, or a related field and completion of a graduate-level course, research project, or internship. Completion of a graduate-level course, research project, or internship involving each of the following:1. ETL (Extract, Transform, Load) processes2. Statistical analysis using R and Stata3. Quantitative analysis techniques: clustering, regression, pattern recognition, and descriptive and inferential statistics4. Communicating and presenting the results of data analyses
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