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Data Annotation Research Jobs in Missouri (NOW HIRING)

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Data Annotation Research information

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What are the key skills and qualifications needed to thrive as a data annotation researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.

What are some common challenges faced in data annotation research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

What are popular job titles related to Data Annotation Research jobs in Missouri?

For Data Annotation Research jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Data Annotation Research jobs in Missouri look for?

The top searched job categories for Data Annotation Research jobs in Missouri are:

Infographic showing various Data Annotation Research job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Full-time

Posted 17 days ago


Hunter Engineering Company rating

9.3

Company rating: 9.3 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

13th of 499 rated machine equipment manufacturers


Job description

Looking to build your career with a company that values innovation, stability, and people? Join our dedicated team as a Data Science Co-Op in Bridgeton, MO!

Since 1946, Hunter Engineering has been aligning cutting-edge technology with a strong commitment to quality. As a family-owned, American-made company, Hunter is the global leader in automotive service equipment, with our products used in over 130 countries by top vehicle manufacturers, tire companies, and service centers.

Were proud to be recognized as a Best Places to Work finalist by the St. Louis Business Journal for five consecutive years (2022 2026) a testament to our commitment to our people. Here, employees are supported, challenged, and take pride in their work. We offer exceptional benefits, a healthy work-life balance, and meaningful opportunities for professional growth.

If youre ready to join a team thats shaping the future of automotive service, read on.

As a Data Science Co-Op, you will be responsible for the research and development of various features based on Machine Learning. The co-op will work primarily on a Windows PC with Python while most of the machine learning training is done on a Linux machine. Our goal is to provide an experience that will be an important, effective first step in the career of a future engineer.

This position is for a Spring 2027 Co-Op, with a start date of January 2027 and an end date of May 2027.

What Youll Do:

  • Train, test, and evaluate deep learning models.
  • Data annotation and manipulation. An example annotation program would be the use of Label Studio to identify and tag objects in images.
  • Create and use PowerShell and Python scripts to acquire and organize data.
  • Create and use VBA scripts in Excel as part of data evaluation.
  • Create and use Python programs to clean and evaluate data.
  • Work with source control tools like GIT to save and control data.
  • Document frequently used processes for others to duplicate.
  • Update training, test, and validation data used for a specific ML model.
  • Work with an AI library like TensorFlow or PyTorch.
  • Configure and use a Linux PC to shorten ML model training times.
  • Experiment with ML models and data to improve results.
  • Software design and testing.
  • Additional duties as assigned.

What Youll Bring:

  • Minimum 3.0 GPA (must be on resume)
  • Major studies in Computer Science or Computer Engineering
  • Programming experience
  • Excellent communication skills

What We Offer:

  • Real-world experience
  • Off-campus team bonding/appreciation event
  • Free Onsite Fitness & Recreation Center

Join us in our mission to Align People and Innovation to Drive Excellence!

  • Make Lives Better Together
  • Take Pride in the Extraordinary
  • Define the Standard

Hunter Engineering does not provide immigration-related sponsorship for this role. Please do not apply for this role if you will need immigration sponsorship (e.g., H-1B, TN, STEM OPT) now or in the future.


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