Data Scientist, Product Analytics

Job Description

About the Role

As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products across our entire family of applications including Facebook, Instagram, Messenger, WhatsApp, and Oculus. You will apply your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, helping define experiences for billions of people and hundreds of millions of businesses worldwide. You will collaborate with cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, and Finance to solve product and business challenges, influence product strategy, and ensure impactful product development. Joining Meta means becoming part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.

Key Responsibilities

Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
Apply technical expertise with quantitative analysis, experimentation, data mining, and data presentation to develop strategies for products serving billions of people and hundreds of millions of businesses.
Identify and measure the success of product efforts through goal setting, forecasting, and monitoring key product metrics to understand trends.
Define, understand, and test opportunities and levers to improve the product, driving roadmaps through insights and recommendations.
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.).
Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience.
Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R).
Master's or Ph.D. Degree in a quantitative field.