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Data Annotation Research Jobs in Tennessee (NOW HIRING)

... data-driven performance management while ensuring regulatory compliance and service excellence ... M., or equivalent degree. Fellowships can be purely research-oriented experiences, and ...

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

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.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

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.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

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 popular job titles related to Data Annotation Research jobs in Tennessee? For Data Annotation Research jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Data Annotation Research jobs? Cities in Tennessee with the most Data Annotation Research job openings:
Senior Image Data Scientist-Center for Bioimage Informatics

Senior Image Data Scientist-Center for Bioimage Informatics

St. Jude Children's Research Hospital

Memphis, TN • On-site

$86K - $154K/yr

Full-time

Posted 21 days ago


St. Jude Children's Research Hospital rating

8.4

Company rating: 8.4 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

61st of 1,004 rated hospitals


Job description

The Center for Bioimage Informatics at St. Jude Children's Research Hospital is seeking two Senior Image Data Scientists to design, develop, validate, document, and operate image-analysis pipelines and visualization solutions for biomedical imaging research. This role works closely with investigators, software engineers, data scientists, imaging facility scientists, and biostatisticians to translate scientific questions into reproducible, scalable analysis workflows using modern image analysis, statistical, computer vision, and machine learning approache
The successful candidate will support image data management, maintain analysis software and repositories, evaluate new methods and tools, and provide technical consultation and training to research teams. This role also serves as a project lead to coordinate image-analysis efforts, align related projects, and contribute to shared CBI infrastructure that supports routine and advanced bioimage analysis.
Applicant Statement:
Applicants are encouraged to include a brief cover letter or supplemental statement with a link to representative work, such as a public repository, napari plugin, published pipeline, or comparable artifact. The statement should briefly describe one end-to-end image-analysis project or software tool the applicant has owned in production, including the biological or scientific question, data scale, methods or model used, pipeline design, validation approach, user adoption, and resulting impact.
Preferred Qualifications:
  • PhD in a relevant quantitative, computational, biomedical, or scientific field.

  • Experience developing, validating, and maintaining image-analysis pipelines for biological or medical imaging data.

  • Strong programming skills in Python and experience with modern computer vision, machine learning, deep learning, or statistical image-analysis methods.

  • Experience with emerging AI methods relevant to bioimage analysis, including vision transformers, foundation models, generative AI, large language models (LLMs), or agentic AI tools.

  • Experience with scalable and reproducible scientific workflows (e.g., Snakemake, Nextflow), containers, version control, and HPC or cloud environments.

  • Demonstrated experience using modern bioimaging tools, data standards, and open-source ecosystems such as napari, ImageJ/Fiji, Cellpose, SAM-family and related foundation segmentation models, QuPath, BioFormats, OME-Zarr/NGFF, or similar platforms.

  • Experience with large image data volumes, image data management, quality control, benchmarking, annotation strategies, and method evaluation.

  • Demonstrated ability to collaborate with research teams, communicate technical results clearly, write user-facing documentation, and provide training through courses, workshops, seminars, or similar formats.

  • Evidence of technical leadership, such as leading multi-lab projects, contributing to shared infrastructure, publishing methods, or contributing to open-source scientific software.

Minimum Education and/or Training:
  • Bachelor's degree in applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering or related field required.
  • Master's degree preferred.

Minimum Experience:
  • Minimum Requirement: Bachelor's degree with 3+ years of work experience in relevant area (e.g., applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering) required.
  • Experience Exception: Master's degree with 1+ years of relevant experience.
  • Experience in image analyses, image data management, and programming (e.g., Python, R, Matlab, Java, C/C++).
  • Experience in image analysis platforms (e.g., ImageJ/Fiji, CellProfiler), scientific computing, scientific data visualization, scientific computer code optimization and evaluation in an HPC environment, development of algorithms, statistical methods or scientific software, working with large image data volumes, biological/medical imaging preferred.
  • Proven performance in earlier role/comparable role.

Compensation
In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of the compensation range for this role. This is an estimate offered in good faith and a specific salary offer takes into account factors that are considered in making compensation decisions including but not limited to skill sets, experience and training, licensure and certifications, and other business and organizational needs. It is not typical for an individual to be hired at or near the top of the salary range and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current salary range is $86,320 - $154,960 per year for the role of Senior Image Data Scientist-Center for Bioimage Informatics.
Explore our exceptional benefits!
St. Jude is an Equal Opportunity Employer
No Search Firms
St. Jude Children's Research Hospital does not accept unsolicited assistance from search firms for employment opportunities. Please do not call or email. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and approved by HR will result in no fee being paid in the event the candidate is hired by St. Jude.

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