2027 Summer Intern- Information Technology

Diversified Gas & Oil Corporation•Birmingham, AL

About The Position

We are seeking a passionate and talented Engineering and Data Science Intern to join our team. This role is ideal for students or recent graduates majoring in engineering, computer science, data science, or related fields who are eager to apply their expertise in modern techniques to real-world projects. Possible Intern Projects include SCADA alarm management, Asset location Geo Fence efforts, Tank Leak detection tuning, AI agent for customer service knowledgebase, and other AI Accounting & Energy projects.

Requirements

  • Must be currently enrolled in a college/university program at the time of internship
  • Self-starter with a passion for learning and a strong work ethic
  • Eagerness to contribute in a team-oriented environment
  • Excellent written and verbal communication skills

Nice To Haves

  • Currently pursuing or recently completed a degree in Engineering, Data Science, Computer Science, or a related field.
  • Proficiency in programming languages.
  • Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and/or data visualization tools (e.g., Tableau, Power BI).
  • Knowledge of cloud computing platforms like AWS, Azure, or Google Cloud.
  • Strong problem-solving and communication skills, with an eagerness to learn and apply new concepts in real-world scenarios.
  • Experience with Database technologies.
  • Understanding of big data tools (e.g., Apache Spark, Hadoop).

Responsibilities

  • Conduct research on cutting-edge AI technologies, frameworks, and best practices, and help integrate them into existing workflows.
  • Work with large datasets to uncover trends, patterns, and actionable insights that drive decision-making.
  • Assist in the development and integration of AI tools and platforms into internal systems and processes.
  • Write and optimize code for AI models, ensuring efficiency and scalability.
  • Work closely with cross-functional teams, including data engineers, product managers, and stakeholders, to understand project requirements and deliver solutions.
  • Prepare detailed documentation of models, pipelines, and workflows for internal use and knowledge sharing.
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