Data Science Co-Op

Hunter Engineering Company•Bridgeton, MO

12h•Onsite

About The Position

Looking to build your career with a company that values innovation , stability , and people ? Join our dedicated team as a Data Science Co-Op in Bridgeton, MO ! Since 1946, Hunter Engineering has been aligning cutting-edge technology with a strong commitment to quality. As a family-owned , American-made company, Hunter is the global leader in automotive service equipment, with our products used in over 130 countries by top vehicle manufacturers, tire companies, and service centers. Were proud to be recognized as a Best Places to Work finalist by the St. Louis Business Journal for four consecutive years (2022 2025) a testament to our commitment to our people. Here, employees are supported, challenged, and take pride in their work. We offer exceptional benefits, a healthy work-life balance, and meaningful opportunities for professional growth. If youre ready to join a team thats shaping the future of automotive service, read on. As a Data Science Co-Op , you will be responsible for the research and development of various features based on Machine Learning. The co-op will work primarily on a Windows PC with Python while most of the machine learning training is done on a Linux machine. Our goal is to provide an experience that will be an important, effective first step in the career of a future engineer. This position is for a Summer/Fall 2026 Co-Op, with a start date of May 2026 and an end date of January 2027.

Requirements

Minimum 3.0 GPA (must be on resume)
Major studies in Computer Science or Computer Engineering
Programming experience
Excellent communication skills

Responsibilities

Train, test, and evaluate deep learning models.
Data annotation and manipulation. An example annotation program would be the use of Label Studio to identify and tag objects in images.
Create and use PowerShell and Python scripts to acquire and organize data.
Create and use VBA scripts in Excel as part of data evaluation.
Create and use Python programs to clean and evaluate data.
Work with source control tools like GIT to save and control data.
Document frequently used processes for others to duplicate.
Update training, test, and validation data used for a specific ML model.
Work with an AI library like TensorFlow or PyTorch.
Configure and use a Linux PC to shorten ML model training times.
Experiment with ML models and data to improve results.
Software design and testing.
Additional duties as assigned.