Technical Principal

Meta Meta · Big Tech · Menlo Park, CA +1 · Remote

Design and build operational processes to protect businesses and users across Meta products, leveraging quantitative analysis, data mining, and data visualization to identify trends and implement solutions at scale. Work with cross-functional teams to build tools, anticipate and mitigate threats, perform statistical modeling, and manage complex projects from ideation to execution. Develop reporting, monitor metrics, and drive process improvements.

What you'd actually do

  1. Design and build operational processes that protect businesses and users across Meta products.
  2. Apply expertise in quantitative analysis, data mining, and data visualization to identify trends and implement solutions at scale.
  3. Work with Engineering, Product, and Data Science teams to identify and build tools that improve performance of our systems.
  4. Anticipate and predict potential threats to operations and platform, design and build solutions to protect against these threats, and then implement and enforce these systems at scale.
  5. Perform statistical modeling and statistical regression analysis to construct business patterns and trends.

Skills

Required

  • Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, Applied Sciences, Mathematics, Physics or related field
  • five years of progressive, post baccalaureate work experience
  • quantitative analysis
  • risk analysis
  • advanced analysis with large data sets
  • SQL
  • Excel
  • PHP, Python, or Perl
  • Building data pipelines
  • Reporting systems
  • dynamic alerts
  • data pipeline architecture
  • Tableau or Unidash
  • business presentation skills

Nice to have

  • complex, multi-faceted problems requiring creative and innovative solution development
  • rapidly assess, analyze, and resolve complicated issues
  • distill that complexity into simple and concise concepts
  • prioritize, re-prioritize, and handle multiple competing priorities
  • resolve and communicate issues with business presentation skills to both technical and non-technical audiences
  • solving problems using data and providing practical business insights
  • leading data-driven projects from definition through interpretation and execution

What the JD emphasized

  • quantitative analysis
  • risk analysis
  • advanced analysis with large data sets
  • data pipeline architecture
  • complex, multi-faceted problems
  • creative and innovative solution development
  • rapidly assess, analyze, and resolve complicated issues
  • distill that complexity into simple and concise concepts
  • prioritize, re-prioritize, and handle multiple competing priorities
  • resolve and communicate issues with business presentation skills
  • solving problems using data
  • providing practical business insights
  • leading data-driven projects