Data Scientist, Product Analytics Lead

4 weeks ago

Menlo Park, California, United States META Full time
Job Summary

As a Monetization focused Data Scientist at Meta, you will have the opportunity to help people and businesses make meaningful connections and build premium services across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world.

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 the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.
  • Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.
  • Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
  • Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.
Requirements
  • 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)
Preferred Qualifications
  • Masters or Ph.D. Degree in a quantitative field.
Compensation and Benefits

$173,000/year to $242,000/year + bonus + equity + benefits

Equal Opportunity

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

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