Jude Children's Research Hospital is seeking a Senior Image Data Scientist for their Center for ... annotation strategies, and method evaluation. • Demonstrated ability to collaborate with research ...
Jude Children's Research Hospital is seeking a Senior Image Data Scientist for their Center for ... annotation strategies, and method evaluation. • Demonstrated ability to collaborate with research ...
Senior Image Data Scientist-Center for Bioimage Informatics
Memphis, TN · On-site
$86K - $154K/yr
Experience with large image data volumes, image data management, quality control, benchmarking, annotation strategies, and method evaluation. * Demonstrated ability to collaborate with research teams ...
Senior Image Data Scientist-Center for Bioimage Informatics
Memphis, TN · On-site
$86K - $154K/yr
Experience with large image data volumes, image data management, quality control, benchmarking, annotation strategies, and method evaluation. * Demonstrated ability to collaborate with research teams ...
... data-rich research environment with established infrastructure for multi-institutional data aggregation, curation, and large-scale annotation. St. Jude Children's Hospital has incredible high ...
... data-rich research environment with established infrastructure for multi-institutional data aggregation, curation, and large-scale annotation. St. Jude Children's Hospital has incredible high ...
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?
| Aspect | Data Annotation Research | Data Labeling Specialist |
|---|---|---|
| Credentials | Typically requires a background in data science, research methods, or related fields | Often requires basic technical skills and experience with labeling tools |
| Work Environment | Research labs, tech companies, or remote research teams | Data centers, tech companies, or remote labeling teams |
| Industry Usage | Used in AI/ML research, developing annotation methodologies | Used in preparing datasets for machine learning models |
| Search & Comparison Intent | Understanding research-focused roles in data annotation | Looking 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 job categories do people searching Data Annotation Research jobs in Tennessee look for? The top searched job categories for Data Annotation Research jobs in Tennessee 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
Memphis, TN • On-site
Full-time
Posted 14 days ago
St. Jude Children's Research Hospital rating
8.6
Based on 12 frontline employees who took The Breakroom Quiz
41st of 1,051 rated hospitals
Job description
Job Summary:
St. Jude Children's Research Hospital is seeking a Senior Image Data Scientist for their Center for Bioimage Informatics to design and operate image-analysis pipelines for biomedical research. The role involves collaborating with various scientific teams to develop scalable analysis workflows and manage image data effectively.
Responsibilities:
• Design, develop, validate, document, and operate image-analysis pipelines and visualization solutions for biomedical imaging research.
• Support image data management, maintain analysis software and repositories, evaluate new methods and tools, and provide technical consultation and training to research teams.
• Serve 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.
Qualifications:
Required:
• Bachelor's degree in applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering or related field required.
• 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 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.
Preferred:
• 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.
Company:
St. Founded in 1962, the company is headquartered in Memphis, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
St. Jude Children's Research Hospital is seeking a Senior Image Data Scientist for their Center for Bioimage Informatics to design and operate image-analysis pipelines for biomedical research. The role involves collaborating with various scientific teams to develop scalable analysis workflows and manage image data effectively.
Responsibilities:
• Design, develop, validate, document, and operate image-analysis pipelines and visualization solutions for biomedical imaging research.
• Support image data management, maintain analysis software and repositories, evaluate new methods and tools, and provide technical consultation and training to research teams.
• Serve 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.
Qualifications:
Required:
• Bachelor's degree in applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering or related field required.
• 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 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.
Preferred:
• 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.
Company:
St. Founded in 1962, the company is headquartered in Memphis, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
What St. Jude Children's Research Hospital employees say
Pay
Benefits
Hours and flexibility
Workplace
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About St. Jude Children's Research Hospital
Sourced by ZipRecruiter
Industry
Health care and social assistance
Company size
1,001 - 5,000 Employees
Headquarters location
Memphis, TN, US
Year founded
1962