The goal of this work is to improve the accuracy of color prediction using machine learning (MF), Data Science and Data Analytics for the GSC Color Lab at Sherwin-Williams.
Requirements
- Experience in Python, SQL, Data Visualization Tools (Tableau)
- Familiarity with Machine Learning Techniques
- Understanding of statistical modeling, data wrangling, data cleaning and data transformation
- Pursuing a bachelor's degree in data science
- Any color theory or color data knowledge is a plus
Responsibilities
- use data science to help develop machine learning models for color prediction
- Predicting the color produced from a given pigmentation formula in a paint is a key function of the GSC Color lab
- improve the accuracy of these predictions using machine learning (MF), Data Science and Data Analytics
- Students will be assigned to and will be given a mentor.
- Interns will also be given a Technical Project in which they will present at the end of their assignment.
- Students will be active participants on a project team and will have periodic reviews to evaluate their performance.
- Students will participate in a number of special networking and learning events throughout their assignment.
Other
- Must be currently enrolled in a Bachelor’s Degree program in Science, Technology, Engineering or Mathematics (“STEM”) at the time of the internship program
- Must be at least eighteen (18) years of age
- Must be legally authorized to work in the country of employment without needing sponsorship for employment work visa status now or in the future
- Must be willing to work up to 40 hours per week for a total of 12 week, with or without reasonable accommodation
- Must have a minimum of 2.8 GPA
