Data Science Intern at DNV

Wayne State University; Houston (TX); On-site; USD 20,664 - 34,440; Full time

Job summary

A technology consulting firm is seeking Data Science Interns for Spring 2026 in Houston, TX. This in-person internship focuses on ML model development and data science. Interns will collaborate with cross-functional teams to create machine learning solutions, utilizing Python and frameworks like TensorFlow. Candidates should be pursuing or have a degree in computer science. Experience with machine learning and cloud environments is preferred. Immigration-related employment benefits are not available for this position.

Qualifications

• Currently pursuing a degree or recently graduated in computer science with specialization in data science.
• Experience in Python and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Familiarity with working in cloud environments.

Responsibilities

• Collaborate with cross-functional teams to translate business requirements into machine learning solutions.
• Design, develop, and maintain scalable machine learning models.
• Optimize model performance and accuracy through efficient training techniques.

Skills

Python

Machine learning frameworks

Data preprocessing

Feature engineering

Model evaluation

Communication

Teamwork

Education

Currently pursuing or recently graduated in computer science or related degree

Tools

TensorFlow

PyTorch

scikit-learn

Git

AWS

Job description

About the role

ANB Systems, a DNV Company is looking to hire Data Science Interns for Spring 2026 focused on ML model development, data science and analytics, and product integration as part of ANB’s Data Science team. This role collaborates closely with our Technology Center in India. As a Data Science Intern you will work on eTRACK+ & DRM product development, internal clients across DNV and external clients as required by contracts. You will support projects sourced by other divisions of DNV and contribute to product development and furthering our MLAI capabilities.

This is in-person role 5 days a week at our DNV office in Houston, TX.

What You’ll Do

• Collaborate with cross-functional teams, including Data Analysts, Software Developers, DevOps Engineers, and Product Managers to translate business requirements into highly available machine learning solutions
• Leverage your creative problem-solving skills to design, develop, and maintain scalable and efficient machine learning models using Python and other relevant technologies
• Create and optimize machine learning algorithms that support predictive analytics, artificial intelligence, and software
• Optimize model performance and accuracy by implementing efficient training and validation techniques
• Apply data preprocessing, feature engineering, and model evaluation to ensure model quality and integrity
• Write clean, efficient, maintainable code, and actively engage with team members in code reviews
• Create and maintain technical documentation covering machine learning models, workflows, and methodologies
• Assist and conduct proof of concepts for ANB products such as eTRACK+, DRM, and eTRM

About you

We strongly prefer for you to submit a 1-page cover letter along with your resume when applying

What Is Required

• Currently pursuing a degree or recently graduated in computer science with specialization in data science or similar relevant technical degree
• Experience in Python and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
• Experience with data preprocessing, feature engineering, and model evaluation
• Familiarity with working in cloud environments
• Experience with version control systems (e.g., Git) and familiarity with agile development practices
• Excellent communication and teamwork skills, with the ability to effectively collaborate with cross-functional teams
• We conduct pre-employment drug and background screening

What Is Preferred

• Experience with AWS is preferable

*Immigration-related employment benefits, for example visa sponsorship, are not available for this position*