DATA SCIENCE INTERN

CCAM•Disputanta, VA
•$24 - $30

About The Position

The Data Science Intern will support CCAM’s research programs. Interns will help to ensure that projects are delivered on time, on budget, and with a high standard of quality.

Requirements

  • At least two years of academic credit completed towards a scientific or engineering degree at an accredited university.
  • Must be a rising Junior, Senior, or Graduate student.
  • Academic Major OR Area of Focus: Computer Engineering, Computer Science, Engineering Majors Completed
  • Coursework: Programming 1 & 2, Design of Experiments/Statistics/Statistics for Engineering, Engineering Problem Solving, Technical Writing/Public Speaking
  • Technical/ Programming Skills: Python, C++, C, C#, R, Technical Writing, Proficient in Excel
  • Ability to work independently towards an established goal without continuous oversight or assistance.
  • Ability to quickly grasp key concepts needed to attack difficult engineering and manufacturing problems.
  • Ability to maintain a positive, team-first mentality.
  • Ability to take ownership of projects.
  • Must be qualified for access to technology or intellectual property that is subject to export control requirements without an export control license.
  • Only candidates from CCAM's 5 University Members (Virginia State University, Virginia Commonwealth University, Old Dominion University, University of Virginia, & Virginia Tech) will be selected.

Nice To Haves

  • Passion for development and application of scientific principles.
  • Passion for innovative, creative, technically complicated problem solving.
  • Passion for working outside of your comfort zone.
  • Passion for having fun while learning new things!

Responsibilities

  • Improve understanding of the application of data science principles in manufacturing through: Understanding the principles of advanced data analysis and modeling schemes for manufacturing with emphasis on machine learning principles for image processing.
  • Modification of existing scripts to analyze large data sets for modeling and analysis purposes.
  • Development of scripts to pre-process datasets as needed for various modeling and analysis purposes.
  • Improve critical thinking skills through: Learning new libraries through API documentation and self-experimentation.
  • Exploring literature for ways to improve performance of existing models.
  • Improve technical communication skills through: Formatting and formal reporting and presentation of results
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