Data Science Intern

Austincc

Houston (TX)

Hybrid

USD 20,000 - 30,000

Full time

14 days+

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Job summary

A reputable technology firm is seeking a Data Science Intern to assist in ML model development and analytics as part of their Data Science team. This in-person role in Houston requires collaboration with various teams to design machine learning models and optimize project outcomes. Candidates should be pursuing a degree in computer science or a related field, with skills in Python and machine learning frameworks. The internship offers an excellent opportunity to contribute to innovative projects and gain valuable hands-on experience.

Qualifications

  • Currently pursuing a bachelor's degree in computer science or similar technical degree.
  • Experience with Python and machine learning frameworks.
  • Familiarity with cloud environments and version control systems.

Responsibilities

  • Collaborate with cross-functional teams to develop machine learning solutions.
  • Design and maintain scalable machine learning models using Python.
  • Optimize model performance and accuracy.

Skills

Python
Machine learning frameworks
Data preprocessing
Feature engineering
Model evaluation
Version control systems (Git)
Agile development practices
Cloud environments
Communication skills
Teamwork skills

Education

Currently pursuing degree in computer science with specialization in data science

Tools

TensorFlow
PyTorch
scikit-learn

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*

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