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Paid Internship - Data and Analytics

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Monster Energy

26d ago

🚀 Off-cycle Internship


AI generated summary

  • You must be currently studying Computer Science or related field, have strong analytics skills, a basic understanding of Generative AI, good communication, and be self-motivated.
  • You will assist in implementing data-driven solutions, analyze and interpret data, support data management projects, research emerging technologies, and collaborate with teams for seamless integration.

Off-cycle Internship



  • Reporting to the Data and Analytics team, this Intern position will support data and analytics projects such as data centralization, data lakehouse modeling and execution, data quality automation, and business intelligence report writing.


  • Currently pursuing a degree in Computer Science, Information Technology, Data Science, or related field.
  • Strong analytical and problem-solving skills with a keen interest in data and analytics.
  • Basic understanding of Generative AI concepts and a willingness to learn more about policy implications.
  • Excellent communication skills and ability to work collaboratively in a team environment.
  • Self-motivated with a proactive approach to learning and contributing to projects

Education requirements

Currently Studying

Area of Responsibilities



  • Assist in the development and implementation of data-driven solutions to enhance business processes.
  • Collaborate with the IT team to analyze and interpret data, providing valuable insights for decision-making.
  • Support ongoing and upcoming projects related to data management, including data cleansing and transformation tasks.
  • Work closely with team to understand and contribute to policy development and implementation.
  • Conduct research on emerging technologies and trends in data analytics to provide recommendations for improvement.
  • Participate in team meetings, sharing ideas and insights to contribute to project planning and strategy.
  • Collaborate with cross-functional teams to ensure seamless integration of data solutions into existing systems.


Work type

Full time

Work mode