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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 technical skills, analytical mindset, and product intuition to one of the richest data sets in the world
Collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others
Use data and analysis to identify and solve product development’s biggest challenges
Influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams
Use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Facebook
Help partner teams prioritize what to build, set goals, and understand their product’s ecosystem
Guide teams using data and insights
Focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them
Requirements:
Requires a Bachelor’s degree (or foreign degree equivalent) in Computer Science, Mathematics, Economics, Statistics or related field, and 2 years of experience in the job offered or related occupation
Requires 2 years of experience in the following: Access and extract data from relational databases (SQL) for analyses
Extract and process data for analyses using large scale data processing infrastructures using distributed systems, such as Hadoop, Hive, or MapReduce
Develop reproducible scripts and statistical analyses using Python when advanced techniques are required
Apply machine learning techniques such as clustering, regression, pattern recognition, or descriptive and inferential statistics
Apply statistical techniques to create and analyze A/B tests, including how to properly set up A/B tests and how to determine statistical significance of results
Communicate and present results of data analyses to influence team and company strategy