Data Science Intern: ML, AI, & Enterprise Projects

Crowe; Dallas (TX); On-site; USD 37,000 - 58,000; Full time

Job summary

Crowe offers a data science internship designed to expose you to enterprise data projects in a collaborative setting. You will work under a dedicated mentor and contribute to real data science tasks that can enhance the team portfolio.

Projects include anomaly detection, numerical optimization, and PHI/PII detection in NLP. This internship emphasizes growth, teamwork, and practical impact within Crowe's analytics practice.

Qualifications

• Pursuing a relevant degree in data science, CS, math, or related field.
• Strong Python coding skills and ability to work with data.
• Experience with enterprise data science workflows is a plus.
• Familiarity with Linux, Git, and containerization is preferred.
• Excellent communication and teamwork.

Responsibilities

• Anomaly detection using deep neural networks.
• Numerical optimization applied to problems in manufacturing.
• PII/PHI detection in natural language.
• Framing business problems as data science problems.
• Navigate the full data science lifecycle: research, development, deployment, support.
• Use model selection and training procedures to prevent common errors.
• Create test scenarios and diagnostics.
• Contribute to code reviews and collaborative development.
• Present work clearly to technical and non-technical audiences.

Skills

Python

Data science concepts

Team collaboration

Education

Data Science

Computer Science

Mathematics

Natural or Social Sciences

Relevant additional backgrounds

Tools

Linux

Git

Docker

Kubernetes

CI/CD

Cloud platforms

Job description

Crowe offers a data science internship designed to expose you to enterprise data projects in a collaborative setting. You will work under a dedicated mentor and contribute to real data science tasks that can enhance the team portfolio.

Projects include anomaly detection, numerical optimization, and PHI/PII detection in NLP. This internship emphasizes growth, teamwork, and practical impact within Crowe's analytics practice.