Data Scientist, Analytics

Meta • Menlo Park, CA

8d

About The Position

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.

Requirements

• Requires a Bachelor's degree (or foreign equivalent) in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Physics, or a related field and 4 years of experience in the job offered or in a data science-related occupation
• Requires 4 years of experience involving each of the following:
• Machine learning techniques
• Relational database (SQL or PLSQL)
• Developing in Python
• Quantitative analysis techniques: clustering, regression, pattern recognition and descriptive and inferential statistics
• Communicating and presenting results of data analyses
• and Statistical analysis using Python

Responsibilities

• Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products.
• Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
• Inform, influence, support, and execute our product decisions and product launches.
• The Data Scientist Analytics role has work across the following four areas: Product Operations (Forecasting and setting product team goals, designing and evaluating experiments, monitoring key product metrics, understanding root causes of changes in metrics, building and analyzing dashboards and reports, building key data sets to empower operational and exploratory analysis, and evaluating and defining metrics)
• Exploratory Analysis (proposing what to build in the next roadmap, understanding ecosystems, user behaviors, and long-term trends, identifying new levers to help move key metric, and building models of user behaviors for analysis or to power production systems)
• Product Leadership (influencing product teams through presentation of data-based recommendations, communicating state of business, experiment results, etc. to product teams and spreading best practices to analytics and product teams)
• and Data Infrastructure (working in Hadoop and Hive primarily, sometimes MySQL, Oracle, and Vertica, and automating analyses and authoring pipelines via SQL and Python based ETL framework).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level