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Internship Text Analytics Jobs (NOW HIRING)

Advantest

AI Intern

San Jose, CA · On-site

... be used to analyze, compare, and assess complex technical content at scale. The internship ... Experience working with document-heavy or text-analysis problems (e.g., reviews, reports, proposals ...

T Rowe Price

2026 Fund Accounting Internship

Owings Mills, MD · Hybrid

$15.25 - $19.25/hr

As a team, we perform, process, manage, or analyze financial transactions and information to ensure ... WHAT TO EXPECT AFTER APPLYING 1. You will receive an email and text message to answer a few ...

T Rowe Price

2026 Fund Accounting Internship

Owings Mills, MD · Hybrid

$15.25 - $19.25/hr

As a team, we perform, process, manage, or analyze financial transactions and information to ensure ... WHAT TO EXPECT AFTER APPLYING 1. You will receive an email and text message to answer a few ...

Rogue Fitness

Data Analyst

Columbus, OH · On-site

... analytics experience; new grads with strong relevant coursework, internships, or projects are ... text messages during the recruitment process.

Rogue Fitness

Data Analyst

Columbus, OH · On-site

... analytics experience; new grads with strong relevant coursework, internships, or projects are ... text messages during the recruitment process.

Chatham County, NC

Election Internship

Pittsboro, NC · On-site

$15/hr

We recommend you sign up for text message alerts when you create your account. If you have issues ... Conducts research and data analysis related to voter registration trends, turnout statistics, and ...

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Internship Text Analytics information

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How much do internship text analytics jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for internship text analytics in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Text Analytics, and why are they important?

To thrive as a Text Analytics Intern, you need a solid background in data analysis, natural language processing (NLP), and statistics, often supported by coursework in computer science or a related field. Familiarity with programming languages like Python, machine learning libraries (such as NLTK or spaCy), and data visualization tools is typically required. Strong problem-solving skills, attention to detail, and effective communication help you interpret data and share insights clearly with teams. These skills are crucial for extracting meaningful information from text data and supporting data-driven decisions within the organization.

What is an Internship in Text Analytics?

An Internship in Text Analytics is a temporary position, often taken by students or recent graduates, where individuals gain practical experience working with techniques to extract meaningful information from large volumes of text data. Interns typically learn how to use natural language processing (NLP) tools, analyze textual datasets, and support projects involving sentiment analysis, topic modeling, or information retrieval. These internships provide hands-on exposure to real-world problems, allowing interns to develop their technical skills and understand how text analytics is applied in industries such as marketing, healthcare, or finance.

What is the difference between Internship Text Analytics vs Data Analyst Intern?

AspectInternship Text AnalyticsData Analyst Intern
Required SkillsText processing, NLP basics, data visualizationData analysis, Excel, SQL, basic statistics
Work EnvironmentTech companies, research labs, marketing firmsBusiness, finance, healthcare sectors
Common UsageAnalyzing unstructured text data, sentiment analysisInterpreting structured data, reporting

Internship Text Analytics focuses on analyzing unstructured text data using NLP techniques, while Data Analyst Interns work primarily with structured datasets and statistical tools. Both roles are common in tech and business environments, but they emphasize different data types and skills.

What types of projects can an intern expect to work on in a Text Analytics internship?

As a Text Analytics intern, you can expect to work on projects involving data cleaning, natural language processing, and sentiment analysis. Typical tasks may include extracting insights from large datasets, building or improving machine learning models, and visualizing textual data to support business decisions. Interns often collaborate closely with data scientists, engineers, and business analysts, gaining exposure to real-world applications and agile development environments. These projects provide hands-on experience with industry-standard tools and help you develop both technical and communication skills.
More about Internship Text Analytics jobs
What cities are hiring for Internship Text Analytics jobs? Cities with the most Internship Text Analytics job openings:
What are the most commonly searched types of Text Analytics jobs? The most popular types of Text Analytics jobs are:
What states have the most Internship Text Analytics jobs? States with the most job openings for Internship Text Analytics jobs include:
What job categories do people searching Internship Text Analytics jobs look for? The top searched job categories for Internship Text Analytics jobs are:
Internship Text Analytics jobs near you
Infographic showing various Internship Text Analytics job openings in the United States as of July 2026, with employment types broken down into 1% Internship, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
AI Intern

AI Intern

Advantest

San Jose, CA • On-site

Full-time

Re-posted 17 days ago

Job description

Description
Advantest America, a global leader in Semiconductor Test and Measurement, is seeking a motivated and innovative engineering student to explore cutting-edge applications of machine learning and generative AI. This internship provides hands-on experience working with emerging
AI systems and integrating them into Advantest's advanced testing
platforms.

Location: Austin, TX or San Jose, CA (headquarters)

Role Overview
In this role, you will contribute to research and prototyping efforts focused on LLM-powered reasoning and evaluation systems. You will explore how retrieval-augmented generation (RAG) and agentic workflows can be used to analyze, compare, and assess complex technical content at scale. The internship emphasizes building AI systems that support decision-making, qualitative judgment, and structured feedback in real-world engineering and research environments.


You will work with unstructured and semi-structured documents, design multi-step reasoning pipelines, and evaluate system behavior against domain-specific expectations and constraints.

Key Responsibilities

  • Design and implement multi-step agentic workflows for analyzing and evaluating technical content.
  • Develop RAG-based pipelines that combine internal documentation and reference materials with LLM reasoning.
  • Build AI agents capable of:
    • Comparing proposed ideas or approaches against known solutions or baselines
    • Identifying conflicts, gaps, redundancies, or lack of novelty
    • Producing structured assessments and constructive feedback
  • Experiment with prompting strategies, planning, reflection, and tool usage to improve reasoning quality and consistency.
  • Evaluate and iterate on system performance using qualitative and semi-quantitative metrics.
  • Collaborate with engineers and researchers to translate ambiguous evaluation criteria into actionable AI workflows.

Requirements:

  • Currently enrolled in a BS or MS program in Computer Science, Electrical Engineering, or a related field
  • Strong programming skills in Python
  • Hands-on experience with LLMs, including prompt design and experimentation
  • Familiarity with retrieval-augmented generation (RAG) concepts (e.g., embeddings, vector search, context assembly)
  • Experience or coursework involving multi-step workflows, pipelines, or agent-based systems
  • Strong written and verbal communication skills, especially for explaining technical decisions
  • Ability to work independently and communicate technical ideas clearly

Additional Skills Preferred (but not required):

  • Experience with agent orchestration frameworks (e.g.,LangGraph, LangChain, custom agent loops)
  • Exposure to LLM evaluation techniques, including rubric-based scoring, pairwise comparison, or ranking tasks
  • Experience working with document-heavy or text-analysis problems (e.g., reviews, reports, proposals, research papers)
  • Familiarity with semantic similarity, novelty detection, or content comparison techniques
  • Interest in building AI systems that support human judgment and decision-making, not just generation
  • Comfort working with imperfect data, evolving requirements, and subjective evaluation criteria

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