Beyonders 2024 Summer Program - Data Science

Program Overview

The Beyond Limits Summer Internship program offers a unique opportunity to explore the world of Artificial Intelligence through an immersive experience. Participants will be imbedded in our current full-time teams of designers, programmers, and developers to help conceive new concepts, solve real business issues, and work with some of the industry’s top talent.

This internship is a F/T role that spans 8-10 weeks over the summer and will run from mid-June through mid-August of 2024. In addition to their projects, participants will gain additional knowledge and networking opportunities through technical speaker series, development workshops, and social events as part of the internship. 

Ideal candidates should possess a background in one of the following technical areas: data science, artificial intelligence, cognitive computing, machine learning, Knowledge engineering, or natural language processing. Candidates with backgrounds in applied sciences or engineering a plus.

Additionally, candidates should be flexible and adaptable to their work; have the ability to work in a team environment and be highly collaborative; and be naturally curious and innovative in solution solving.

Program Eligibility Requirements

• Must be 18 years old at time of start
• Must be legally authorized to work in the U.S.
• Must be available to work F/T for the entire duration of the program
• Must be currently enrolled in an accredited university obtaining a bachelors degree or higher with at least one semester or quarter left at time of start
• Must be able to provide own housing and transportation to/from job site throughout the duration of internship assignment
• All interested candidates must apply through Beyond Limits' website in order to be considered
• Programming experience in Python, R, and/or Matlab

Preferred Qualifications

• 1-2 years of experience solving data science problems
• Experience working in an industry setting
• Domain expertise in energy, healthcare, finance, and/or logistics
• Research experience with high impact publications
• Familiar with common data science techniques, such as:
  • Linear / logistic regression
  • Decision tree algorithms (e.g. random forest)
  • Clustering algorithms (e.g. K-means)
  • Support vector machine (SVM)
  • Artificial neural networks
• Experience with common data science tools, such as: 
  • Numpy
  • Pandas
  • Matplotlib
  • Plotly