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Remote Medical Data Annotation Jobs in Edmonds, WA

Cisco

Director, Data Operations

Seattle, WA · On-site +1

$207K - $267K/yr

Anywhere in the US Hybrid if in San Jose CA or San Francisco, California Remote if no office is ... S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical ...

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Remote Medical Data Annotation information

What are the key skills and qualifications needed to thrive as a Remote Medical Data Annotation Specialist, and why are they important?

To excel as a Remote Medical Data Annotation Specialist, you need a background in medical terminology, attention to detail, and familiarity with healthcare data formats, often supported by a degree or certification in a health-related field. Proficiency with annotation tools, electronic health record (EHR) systems, and data management platforms is typically required. Strong communication, time management, and analytical thinking are essential soft skills for accurate labeling and collaboration with remote teams. These competencies ensure that annotated data is reliable and precise, which is crucial for developing effective medical AI systems and supporting clinical research.

What are some common challenges faced by remote medical data annotation specialists, and how can they be overcome?

Remote medical data annotation specialists often encounter challenges such as maintaining data accuracy, understanding complex medical terminology, and managing communication with clinical teams. To overcome these, it's important to stay up-to-date with medical guidelines, participate in regular training sessions, and use collaboration tools to clarify medical ambiguities with colleagues or supervisors. Additionally, creating a structured daily workflow and setting up a distraction-free workspace can help maintain focus and accuracy when working with sensitive healthcare data.

What is the difference between Remote Medical Data Annotation vs Remote Medical Transcription?

AspectRemote Medical Data AnnotationRemote Medical Transcription
CredentialsBasic medical knowledge, attention to detailMedical terminology knowledge, typing skills
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageAI training, healthcare data labelingMedical record documentation
Common Search IntentData annotation, AI training jobsTranscription, medical record jobs

Both roles are remote and involve healthcare data, but Medical Data Annotation focuses on labeling data for AI models, while Medical Transcription involves converting audio recordings into written reports. Understanding these differences helps job seekers find the right fit in the healthcare data industry.

What is remote medical data annotation?

Remote medical data annotation involves labeling or tagging medical data—such as images, text, or audio—using specialized software, all while working from a location outside of a traditional office or lab. Annotators help create high-quality datasets that are essential for training machine learning models used in medical research and diagnostics. This work can include identifying areas of interest on medical scans, categorizing patient records, or transcribing audio notes. Remote annotation roles require attention to detail, a basic understanding of medical terminology, and adherence to privacy regulations like HIPAA. The position is vital for advancing artificial intelligence in healthcare.
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Remote Medical Data Annotation jobs near you
Deep Learning Quality Specialist

Deep Learning Quality Specialist

Carbon Robotics

Seattle, WA • On-site, Remote

Other

Posted 22 days ago

Job description

As a Deep Learning Quality Specialist at Carbon Robotics you'll be responsible for maintaining our expanding dataset of high resolution images that feed our computer vision algorithms. You will develop a deep understanding of our data annotation practices and assist in diagnosing & fixing complex deep learning models to ensure our products are robust & reliable. You will help the Deep Learning team by performing field tests and identifying issues with models. You'll do whatever it takes - which includes going to the farm - to ensure our customers have reliable and safe products.

Our office is based in Seattle, WA, but this role can be fully remote. 

What you'll do:

  • Audit data to ensure clean and appropriate datasets
  • Look through imagery and correct labels and classifications then give feedback to labelers
  • Work closely with support to help investigate issues and determine what is needed to insure data integrity
  • Review data irregularities detected by automated tooling
  • Validate solutions, document results and record customer feedback
  • Translates field tests, model issues and analyze customer feedback
  • Prepare cases for field personnel to review labels/predictions
  • Help the Deep Learning team prioritize tasks based on impact to customer satisfaction

Knowledge, Skills, and Abilities for Success:

  • Education or professional experience in agronomy & farming or data annotation
  • Highly motivated, independent thinker with great problem solving skills
  • Highly organized with excellent time management to juggle multiple priorities at the same time
  • Collaboration skills to work with customers and internal teams simultaneously
  • High level of attention to detail & the ability to think strategically
  • Detail-oriented, with proven ability to deliver accurate reporting
  • Intermediate to advanced Google Suite and Confluence skills desired
  • Ability to assess high risk situations & make safe independent decisions on a risk based process
  • Traveling required 10-15%

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