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Internship Data Classification Jobs (NOW HIRING)

Athenago

Data Science Intern

Wilmington, DE

Strong foundation in statistics and machine learning concepts (regression, classification ... Previous internship or project experience demonstrating practical data science applications.

Cypress HCM

Data Science Engineer

Austin, TX · Hybrid

$65 - $69.72/hr

... classification. * Work closely with Cyber Fraud Investigations and Data Engineering teams to ... This role is not suitable for entry-level candidates or interns. Compensation: * $65.00 to $69.72 ...

Conversica, Inc

Data Scientist

Seattle, WA · On-site

... interns in the areas of natural language processing, natural language generation, and deep learning ... Your scope will reach from text classification problems over big data analytics to A/B testing and ...

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Internship Data Classification information

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How much do internship data classification jobs pay per hour?

As of Aug 5, 2026, the average hourly pay for internship data classification in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Internship Data Classification vs Data Analyst?

AspectInternship Data ClassificationData Analyst
Required CredentialsTypically pursuing or recent graduate, some knowledge of data conceptsBachelor's degree in data-related field, some roles require certifications
Work EnvironmentInternship setting, entry-level tasks, supervisedFull-time, professional environment, independent analysis
Employer & Industry UsageInternship programs in tech, finance, healthcareAcross industries, including tech, finance, marketing
Search & Comparison IntentLearning about entry-level data roles, internshipsUnderstanding data analysis careers, job requirements

Internship Data Classification is an entry-level, supervised role focused on learning data categorization tasks during an internship. In contrast, a Data Analyst is a full-time professional responsible for analyzing data to inform business decisions. While both roles involve working with data, internships are designed for skill development, whereas data analysts perform independent, ongoing analysis in a professional setting.

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What are the most commonly searched types of Data Classification jobs? The most popular types of Data Classification jobs are:
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Internship Data Classification jobs near you

Jr. Data Scientist 00021

West Coast Consulting

Westbrook, ME

$45 - $48/hr

Other

Medical, Life

Posted 28 days ago

Job description

Job Description Hybrid -Westbrook, ME Job Description: The Machine Intelligence team in R&D is looking for an entry-level Data Scientist to develop machine learning solutions for the hematology analyzers. In this role, you will work on classification and clustering problems on tabular data, with solutions deployed on edge hardware in our analyzer platforms. You will work under the supervision of a senior data scientist who will guide your technical development and project execution.

We are looking for a curious, adaptable team player eager to build foundational skills in applied machine learning. What you can expect: Develop classification and clustering models on tabular data to support hematology analyzer capabilities Contribute to model development, evaluation, and iteration under the guidance of a senior data scientist Partner with senior team members to understand requirements, explore data, and validate model performance Document your work clearly so it can be reviewed, reproduced, and built upon by the team Deploy your solutions to edge hardware What you need to succeed: 0-2 years of experience applying machine learning to real-world problems (internships, research, and coursework projects count) Strong working knowledge of Python and common data science libraries (pandas, scikit-learn, NumPy) Solid foundation in statistics, machine learning, and algorithms Demonstrated understanding of classification and clustering methods for tabular data, including when to apply which approach and how to evaluate results Curiosity about the data and the underlying generating processes - a habit of asking "why" before reaching for a model A growth mindset and willingness to learn from more senior team members Ability to communicate analyses and results clearly to your immediate team Bachelor's degree in a quantitative field (statistics, computer science, math, engineering, or related); advanced degree a plus Nice to have: Exposure to deploying ML models on resource-constrained or edge hardware Familiarity with model optimization techniques (quantization, ONNX, TFLite) Experience with version control (Git) and collaborative software development practices Experience modeling data for medical, diagnostic or life sciences applications

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