Machine Learning & Predictive Modeling Internship Summer 2026
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Job Location:
Glen Raven, NC - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Department:
Job Summary
Glen Raven is seeking a technically strong summer intern to design and implement a machine-learning model that predicts fabric performance in the PPE Sector using historical lab data. This role is project-driven and hands-on with responsibility spanning data exploration feature engineering model development and evaluation.
Description:
Build end-to-end machine learning pipelines to predict fabric performance metrics from historical testing data
Perform data cleaning feature engineering and exploratory analysis on large structured datasets housed in a data lake
Evaluate and compare modeling approaches (e.g. regression tree-based models ensemble methods simulation-informed models)
Validate model performance using appropriate metrics and cross-validation techniques
Collaborate with Product Development and Data Analytics partners to ensure scalable and reproducible workflows
Document model architecture assumptions and limitations for future extension
Deliver a final technical readout and working prototype at the conclusion of the internship
Location:
Sunbrella HQ 142 Glen Raven Burlington NC
Remote
Duration:
10 consecutive weeks between May and August with opportunity for extension
Required Candidate Qualifications:
Pursuing a degree in Computer Science Data Science Engineering or a related quantitative field
Strong proficiency in Python and common data science libraries (pandas NumPy scikit-learn etc.)
Solid understanding of machine learning fundamentals statistics and model evaluation
Experience working with structured datasets and version-controlled codebases (Git)
Ability to work independently on an open-ended technical problem
Contact:
John Falkner Talent Acquisition Manager
Required Experience:
Intern
Key Skills
- Microsoft Office
- Public Relations
- Google Docs
- Data Collection
- MailChimp
- Microsoft Word
- Dermal Fillers
- Microsoft Powerpoint
- Research Experience
- Microsoft Excel
- Adobe Photoshop
- Writing Skills
About Company
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