This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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.
Job Responsibility:
Apply quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how Meta users interact with consumer and business products
Mine massive amounts of data and perform large-scale data analysis to extract useful business insights
Develop data pipelines with automated, machine-learning systems that convert noisy core datasets into powerful signals of user behavior
Build models of user behaviors for analysis or to power production systems
Partner with Product and Engineering teams to solve problems and identify trends and opportunities
Design and implement dashboards and reports that track key business metrics and provide actionable insights
Inform, influence, support, and execute our product decisions and product launches by effectively communicating results to cross functional groups
Work across areas of product operations, exploratory analysis, product leadership, and data infrastructure to help shape the future of what we build at Meta
Requirements:
Bachelor's degree (or foreign degree equivalent) in Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences, or a related field and 2 years of experience in the job offered or a related occupation
Experience must include 2 years of experience in the following: Quantitative analysis techniques: clustering, regression, pattern, recognition, or descriptive and inferential statistics
Data analysis and algorithm development
Optimization, probability, statistics, or machine learning
ETL (Extract, Transform, Load) processes
Relational databases and SQL
Large scale data processing infrastructure using distributed systems ( Hive or Teradata)
Experience with data analysis and statistical modeling using the R or Python ecosystems, with packages such as pandas, statsmodels, scikit-learn, tidyverse (dplyr, ggplot2, etc.),R, MATLAB or SAS
Technical presentation skills
Working with cross-functional teams to choose/create metrics and set metric goals
Designing and executing experiments (e.g. A/B tests, country tests, network tests)
Technical presentation skills to influence technical and non-technical audiences (engineers, data scientists, program managers, marketers)