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Internship Natural Language Processing Intern Jobs in Missouri

Leverage Natural Language Processing (NLP) and machine learning to categorize and cluster raw user utterances. Perform sentiment analysis on unstructured text logs to extract actionable product ...

Strong foundation in statistics, modeling, and large‑scale text processing Core Competencies Demonstrates expertise in Natural Language Processing (NLP), Large Language Models (LLM), and generative ...

... natural language processing tools like NLTK for text analytics and sentiment analysis - Implementing neural networks and deep learning methods for advanced AI applications - Managing data quality and ...

AI Software Engineer

California, MO · On-site

$136.80 - $299.30/hr

Develop AI solutions for computer vision, natural language processing, and recommendation systems. * Design, code, and maintain innovative AI algorithms, models, and software applications. * Write ...

... natural language processing tools like NLTK for text analytics and sentiment analysis - Implementing neural networks and deep learning methods for advanced AI applications - Managing data quality and ...

Experience working with predictive analytics, recommendation engines, natural language processing, or generative AI solutions. * Familiarity with cloud-based environments and modern data platforms.

Experience working with predictive analytics, recommendation engines, natural language processing, or generative AI solutions. * Familiarity with cloud-based environments and modern data platforms.

Experience working with predictive analytics, recommendation engines, natural language processing, or generative AI solutions. * Familiarity with cloud-based environments and modern data platforms.

Intern

Kansas City, MO

$14.75 - $19.50/hr

The Internship experience is designed to develop student athletes in discerning their calling and ... the language of sport. Responsibilities: * Build consistent presence at campuses and athletic ...

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Internship Natural Language Processing Intern information

What is the difference between Internship Natural Language Processing Intern vs Data Science Intern?

AspectInternship Natural Language Processing InternData Science Intern
Required CredentialsRelevant coursework in NLP, computer science, or linguistics; basic programming skillsBackground in statistics, mathematics, or computer science; programming skills
Work EnvironmentResearch-focused, often in AI or NLP teams within tech companies or research labsData analysis, modeling, and visualization tasks in tech, finance, or consulting firms
Employer & Industry UsageCommon in AI startups, tech giants, and research institutionsWidely used across tech, finance, healthcare, and consulting industries

Both roles are internship positions requiring programming skills and relevant coursework. NLP Interns focus specifically on language processing tasks, while Data Science Interns work on broader data analysis and modeling projects. The choice depends on your interest in language technologies versus general data analysis.

What job categories do people searching Internship Natural Language Processing Intern jobs in Missouri look for?

The top searched job categories for Internship Natural Language Processing Intern jobs in Missouri are:

What cities in Missouri are hiring for Internship Natural Language Processing Intern jobs?

Cities in Missouri with the most Internship Natural Language Processing Intern job openings:

Infographic showing various Internship Natural Language Processing Intern job openings in Missouri as of August 2026, with employment types broken down into 40% Internship, 33% Full Time, 20% Part Time, and 7% Temporary. Highlights an 87% In-person, and 13% Hybrid job distribution.

Data Scientist - Conversational AI

Jobtailor

Dearborn, MO • On-site

$120 - $150/hr

Other

Posted 16 days ago


Job description

  • NLP & Utterance Analysis: Leverage Natural Language Processing (NLP) and machine learning to categorize and cluster raw user utterances. Perform sentiment analysis on unstructured text logs to extract actionable product insights.
  • AI Response Evaluation & Experimentation: Design methodologies to evaluate the helpfulness, accuracy, and relevance of the AI’s responses. Design and analyze A/B tests to measure the impact of prompt adjustments, model updates, and new feature rollouts.
  • Data Integration & Sanitization: Dive directly into Google Cloud Platform (GCP) to cleanly join and structure mobile, customer support, and vehicle data into robust "Analytical Sandboxes," ensuring strict adherence to data privacy and PII handling standards.
  • Problem Framing & Metric Definition: Act as a strategic partner to Product Managers. Challenge assumptions and define core conversational metrics (e.g., task success rates, user engagement, support deflection).
  • Advanced Visualization & Self-Service: Design, build, and maintain highly intuitive, narrative-driven dashboards using Looker and PowerBI to empower the product team to answer their own day-to-day questions.
  • Bridge the Mobile-to-IVI Gap: Act as the analytical bridge as our digital assistant expands from the Ford app into the vehicle, standardizing mobile data against our emerging in-vehicle data contracts.

Requirements

  • Education: A Master's Degree in a quantitative, technical, or related field (e.g., Data Science, Computer Science, Statistics).
  • Experience: 7+ years of experience in Data Science, Product Analytics, or Applied Machine Learning.
  • "Full-Stack" Capability: Demonstrated ability to act as a bridge between Data Science, Engineering, and Product—taking raw telemetry, applying statistical/ML models, and transforming it into business insights without relying on a central data team for every step.
  • Applied ML & LLM Analytics: Proficiency in Python or R with hands‑on experience in text analytics, clustering, and categorization. Familiarity with LLM evaluation techniques (e.g., prompt effectiveness, hallucination tracking, human-in-the-loop feedback).
  • Expert‑Level SQL & GCP: Highly proficient in writing complex, optimized SQL (Window Functions, CTEs, handling JSON/Nested Data) within Google Cloud Platform (BigQuery) to structure datasets independently.
  • Advanced Visualization: Deep expertise in building scalable business intelligence solutions, semantic layers, and executive‑facing dashboards in Looker and PowerBI.
  • Experimentation: Strong grasp of statistics and experience designing and measuring A/B tests in a product environment.
  • Analytics as Code: Experience with version control (e.g., Git, GitHub) and working in environments where analytics changes go through a formal peer‑review process.
  • Strategic Problem Solving: Comfortable navigating complex, multi‑source data environments. You view data integration as a puzzle to be solved and a strategic enabler for the business.

Core Competencies

Demonstrates expertise in Natural Language Processing, Applied Machine Learning, and Data Analytics, with a strong focus on building advanced visualizations and conducting A/B testing to drive product insights. Proficient in SQL and Google Cloud Platform, capable of integrating and structuring complex datasets while ensuring data privacy standards.

Highest‑signal resume keywords

  • Natural Language Processing
  • Applied Machine Learning
  • Expert‑Level SQL
  • Google Cloud Platform
  • Advanced Visualization

ATS Optimization Keywords

Hard Skills

  • Natural Language Processing
  • Machine Learning
  • SQL
  • Python
  • R
  • Data Analytics
  • A/B Testing
  • Text Analytics
  • Clustering
  • Data Integration

Soft Skills

  • Strategic Problem Solving
  • Collaboration

Industry Keywords

  • Data Science
  • Product Analytics
  • Sentiment Analysis
  • Data Privacy
  • PII Handling

Tools & Technologies

  • Google Cloud Platform
  • Looker
  • PowerBI
  • Git
  • GitHub
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