Data Scientist

Meta•Menlo Park, CA

About The Position

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.

Requirements

Requires a Master's degree (or foreign equivalent) in Computer Science, Engineering, Analytics, Mathematics, Business, Business Administration, or a related field and 1 year of experience in the job offered or in a related occupation
Requires 1 year of experience in the following:
Performing quantitative analysis including data mining on highly complex data sets
SQL
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
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, pattern recognition, or descriptive and inferential statistics

Responsibilities

Devise methods for identifying data patterns and trends.
Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of company products.
Identify data patterns.
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.
Partner with Product and Engineering Teams to solve problems and identify trends and opportunities.
Inform, influence, support, and execute 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 moderate scope where analysis of situations or data requires a review of a variety of factors.