applinity

Data Scientist

at Meta

Location

Menlo Park, CA; Remote, US

Type

full time

Posted

2 months ago

Remote

Yes

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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

  • Collect, organize, interpret, and summarize statistical data in order to contribute to the continued growth of company infrastructure.
  • Apply experience in quantitative analysis and data mining to improve, and optimize across a variety of domains with an emphasis on long-term and strategic initiatives.
  • Work cross-functionally to define priorities and develop business intelligence project roadmaps in synergy with partner teams.
  • Drive execution through fast iteration.
  • Ensure coordination of projects across related workflows to maximize impact and avoid duplication and overlaps.
  • Drive efficient data exploration and modeling.
  • Build pragmatic, scalable, and statistically rigorous solutions to large-scale web, mobile and data infrastructure problems by leveraging or developing statistical and machine learning methodologies.
  • Work on problems of moderate scope where analysis of situations or data requires a review of a variety of factors.
  • Telecommuting from anywhere in the U.S is allowed.

Minimum Qualifications

  • Requires a Bachelor's degree (or foreign equivalent) in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Cognitive Science, or a related field
  • Requires completion of an undergraduate-level course, research project, or internship involving the following:
  • Quantitative Analysis
  • A/B Testing and Research Design
  • Statistical Modeling
  • Data Mining
  • Data Visualization and Storytelling
  • SQL
  • and Python