Data Science Intern — ML & Product Analytics (Houston)

Wayne State University

Houston (TX)

On-site

USD 20,664 - 34,440

Full time

14 days+

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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

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.
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