Data Scientist
Description
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. 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. 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. Work in Hadoop, Hive, MySQL, Oracle, and Vertica. Automate analyses and author pipelines via SQL and Python-based ETL framework.
Qualifications
Requires Doctorate degree in Statistics, Mathematics, Economics, or a related field Completion of a graduate level course, research project, or internship involving each of the following: Performing quantitative analysis including datamining on highly complex data sets Data querying language(s) including SQL Scripting language(s) including Python Statistical or mathematical software including one of the following: R, SAS, or Matlab Applied statistics or experimentation, such as A/B testing, in an industry setting Machine learning techniques ETL(Extract, Transform, Load) processes Relational databases Large-scale data processing infrastructures using distributed systems and Quantitative analysis techniques, including one of the following: clustering, regression, patternr ecognition, or descriptive and inferential statistics
Compensation: $216,571/year to $235,400/year + bonus + equity + benefits