Job 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, 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. Instructions on how to apply, click “Apply to Job” online on this web page.
Data Scientist, Product Responsibilities

Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of Meta products

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 both 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

May be assigned projects in various areas including, but not limited to, product operations, exploratory analysis, product influence, and data infrastructure

Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors

Demonstrate good judgment in selecting methods and techniques for obtaining solutions

In connection with these duties, may apply knowledge of the following: Performing quantitative analysis including data mining on highly complex data sets, Data querying languages, such as SQL, scripting languages, such as Python, or statistical or mathematical software, such as R, SAS, or Matlab, Applied statistics or experimentation, such as A/B testing, in an industry setting, Communicating the results of analyses to product or leadership teams to influence strategy, Machine learning techniques, ETL (Extract, Transform, Load) processes, Relational databases, Large-scale data processing infrastructures using distributed systems, and Quantitative analysis techniques, including clustering, regression, pattern recognition, or descriptive and inferential statistics

Minimum Qualifications

Requires a PhD degree in Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences, or a related field. Position also requires completion of a university-level course/research/project internship/thesis, or 6 months of experience in each of the following:

Machine learning techniques

Working with large data sets and network-based date (TCP or HTTP)

ETL (Extract, Transform, Load) processes

Relational database (SQL or PL*SQL)

Developing in scripting language: PHP, Python, or Perl

Statistical analysis using R, MATLAB, Mathematica, ROOT, SPSS, SAS, or Stata

Large scale data processing infrastructures using distributed systems (Hadoop, Hive, MapReduce, LCG, or MPI)

Quantitative analysis techniques: clustering, regression, patterns recognition, or descriptive and inferential statistics

Communicating and presenting results of data analyses