Remote World - Data Scientist, Product

Client: Remote World

Contract: Internship

Job Description

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. The company is moving beyond 2D screens toward immersive experiences like augmented and virtual reality, aiming to build the next evolution in social technology. Responsibilities for the role include:

• Collecting, organizing, interpreting, and summarizing statistical data to contribute to the design and development of Meta products.
• Applying expertise in quantitative analysis, data mining, and data presentation to understand user interactions with consumer and business products.
• Partnering with Product and Engineering teams to solve problems and identify trends and opportunities.
• Informing, influencing, supporting, and executing product decisions and product launches.
• Working on projects in various areas, including product operations, exploratory analysis, product influence, and data infrastructure.
• Exercising judgment within defined procedures and practices to determine appropriate actions.
• Telecommuting from anywhere in the U.S. is allowed.

Requirements

Qualifications for the position include:

• A Bachelor’s degree (or foreign equivalent) in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Applied Sciences, or a related field.
• Completion of a university-level course, research project, internship, or thesis focusing on:
• Performing quantitative analysis, including data mining on highly complex data sets.
• Data querying language: SQL.
• Scripting language: Python.
• Statistical or mathematical software, such as R, SAS, or Matlab.
• Applied statistics or experimentation, including A/B testing, in an industry setting.
• Machine learning techniques.
• ETL (Extract, Transform, Load) processes.
• Relational databases.
• Large-scale data processing infrastructures using distributed systems.
• Quantitative analysis techniques, including clustering, regression, pattern recognition, or descriptive and inferential statistics.

Additional Information

To apply, click “Apply to Job” online on the designated webpage.

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