Analytics Engineer

$180,217 - $196,900/Yr

Meta - Menlo Park, CA

Full-time - Mid Level

Menlo Park, CA

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About the position

The Analytics Engineer at Meta is responsible for collecting, organizing, interpreting, and summarizing statistical data to contribute to the design and development of Meta products. This role involves applying quantitative analysis and data mining expertise to understand user interactions with both consumer and business products, partnering with Product and Engineering teams to identify trends and opportunities, and providing data-driven strategic guidance for product development.

Responsibilities

• Collect, organize, interpret, and summarize statistical data to contribute to product design and development.
• Apply expertise in quantitative analysis and data mining to understand user interactions with products.
• Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
• Inform, influence, support, and execute product decisions and launches.
• Work on diverse projects including product operations, exploratory analysis, and data infrastructure.
• Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
• Provide data-driven strategic guidance for product development decisions.
• Evaluate investment opportunities and outcomes of initiatives.
• Provide operational analytics support for product launches and performance monitoring.

Requirements

• Master's degree in Data Science, Computer Science, Engineering, Information Systems, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field.
• Experience performing quantitative analysis on complex data sets.
• Proficiency in SQL for data querying.
• Experience with Python as a scripting language.
• Familiarity with statistical or mathematical software such as R, SAS, or Matlab.
• Experience with applied statistics or experimentation, including A/B testing.
• Knowledge of machine learning techniques.
• Experience with ETL (Extract, Transform, Load) processes.
• Familiarity with relational databases.
• Experience with large-scale data processing infrastructures using distributed systems.
• Knowledge of quantitative analysis techniques such as clustering, regression, or descriptive and inferential statistics.

Benefits

• Bonus
• Equity
• Health insurance
• 401k plan
• Paid time off
• Flexible working hours