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, 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
Utilize 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.
* Responsible for defining key product metrics, forecasting and setting product team goals.
* Design and evaluate experiments.
* Monitor key product metrics, understanding 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.
* Perform exploratory analysis.
* Understand ecosystems, user behaviors, and long-term trends.
* Identify new levers to help move key metrics.
* Building models of user behaviors for analysis or to power production systems.
* Influence Product teams through presentation of data-based recommendations.
* Communicate state of business, experiment results to Product teams.

Qualifications
PhD degree (or foreign degree equivalent) in Statistics, Mathematics, Physics, Computer Science, Sociology or related field. Requires completion of a university-level course, research project, internship, or thesis in the following:
* Quantitative analysis, including clustering and regression techniques, pattern recognition, descriptive and inferential statistics, and experimental design (including hypothesis testing)
* Practical experience using querying (e.g. SQL) and scripting (e.g. Python) languages to orchestrate Extract, Transform, and Load (ETL) processes on large-scale relational databases, and performing data mining on highly-complex datasets for the aforementioned analyses
* Practical experience in experimental design, setup and analysis, along with defining key performance indicator and guardrail metrics to enable product teams to run product tests and both track and measure progress against team goals
* Performing structured audits of logged data to recommend product improvements and guide internal teams to prioritize highest impact work based on top business needs
* Practical experience in data risk management, including the design of automated processes to rapidly identify and remediate key gaps that could prevent product teams from hitting their goals and
* Presenting qualitative and quantitative information to technical and non-technical audiences, including the application of machine learning techniques and Artificial Intelligence