GenAI & Data Science Intern (Remote)

Chemour; United States; Remote; USD 3,444,000 - 4,822,000; Full time

Job summary

Chemours is seeking a Generative AI and Data Science Intern to join our AI & Data Science team in Wilmington, with remote work possible for outstanding candidates. You'll build predictive models on Azure platforms and contribute to GenAI solutions across R&D, Finance, Manufacturing, Legal and Environment/Safety.

You will write Python data routines using pandas and scikit-learn, participate in dataset design, and help deploy GenAI apps and hybrid search features.

Qualifications

• Enrollment at an accredited college or university pursuing or recently completed a relevant degree.
• 2+ years of programming experience in Python with pandas and scikit-learn.
• 1+ year practical experience building predictive ML models or GenAI applications.

Responsibilities

• Develop predictive models using Azure platform tools (e.g., Microsoft Fabric, Azure ML Studio).
• Write data preparation and analysis routines in Python using pandas and scikit-learn.
• Participate in dataset design and statistical modeling discussions.
• Design and deploy GenAI solutions and apps into production enterprise environments.
• Collaborate on full-stack development for small applications and efficient UI/UX workflow.
• Apply best practices for designing and delivering GenAI hybrid search.

Skills

Python programming

Pandas

Scikit-learn

GenAI applications

Machine learning models

Full-stack development

Education

Bachelor’s/Master’s/PhD in Data Science/CS/AI/Software Engineering/Computational Chemistry

Tools

React

NodeJS

FastAPI

SQL

Git

CI/CD

Azure

Google Cloud

AWS

Job description

Chemours is seeking a Generative AI and Data Science Intern to join our AI & Data Science team in Wilmington, with remote work possible for outstanding candidates. You'll build predictive models on Azure platforms and contribute to GenAI solutions across R&D, Finance, Manufacturing, Legal and Environment/Safety.

You will write Python data routines using pandas and scikit-learn, participate in dataset design, and help deploy GenAI apps and hybrid search features.