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Data Annotation Jobs in West Virginia (NOW HIRING)

$200K/yr

Define annotation guidelines, taxonomies, and edge-case protocols for each labeling program ... Identify and remediate mislabeled data in existing datasets. * Platform & tooling : Serve as the ...

$65K/yr

Background in data collection, AI, data annotation, or digital operations. * Familiarity with workforce management, ticketing, or project management systems. * Experience supporting macOS ...

Patient Access Representative

Morgantown, WV · On-site

$17.75 - $22.75/hr

Maintain accurate accounts, i.e. required signatures, proper account annotation, current ... Checking in patients, collecting payments, answering phones, scheduling intakes, and data entry.

Patient Access Representative

Morgantown, WV · On-site

$17.75 - $22.75/hr

Maintain accurate accounts, i.e. required signatures, proper account annotation, current ... Checking in patients, collecting payments, answering phones, scheduling intakes, and data entry.

Data Annotation information

What is a data annotation?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

What does a data annotation do?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

What are the key skills and qualifications needed to thrive in data annotation?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

How much money can I make doing data annotation?

Data annotation jobs typically pay between $10 and $20 per hour, depending on the complexity of the task and the employer. Experienced annotators or those working on specialized projects may earn higher rates, especially if they have skills in specific tools or domains. Earnings can vary based on whether the work is freelance, part-time, or full-time, and some platforms offer bonuses for accuracy or speed.

What are the most commonly searched types of Data Annotation jobs in West Virginia?

The most popular types of Data Annotation jobs in West Virginia are:

What are popular job titles related to Data Annotation jobs in West Virginia?

For Data Annotation jobs in West Virginia, the most frequently searched job titles are:

Infographic showing various Data Annotation job openings in West Virginia as of August 2026, with employment types broken down into 63% Full Time, 22% Part Time, and 15% Contract. Highlights an 71% In-person, and 29% Remote job distribution.

Senior Manager, Machine Learning (Data Operations)

Coalition, Inc.
Real Estate • 11 - 50 employees

$200K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 25 days ago


Job description

About the role
Coalition's machine learning models are only as good as the data they're trained on. This role exists to make sure that data is right.

You'll own labeling quality and methodology across Coalition - designing annotation tasks, defining quality frameworks, and ensuring every labeled dataset meets the standard required to ship production ML models. You'll manage our labeling platform (Label Studio), work directly with ML and product teams to structure labeling programs, and oversee outsourced labeling vendors to hit quality and throughput targets.
 

This role reports to the Chief Product Officer and sits at the intersection of product, ML, and operations. You won't manage internal labelers - all annotation work is outsourced - but you will be the single point of accountability for whether Coalition's labeled data is accurate, consistent, and fit for purpose.
Responsibilities
  • Labeling quality & methodology: Define annotation guidelines, taxonomies, and edge-case protocols for each labeling program. Establish gold standard datasets, inter-annotator agreement (IAA) targets, and audit sampling processes. Identify and remediate mislabeled data in existing datasets.
  • Platform & tooling: Serve as the primary user and requirements driver for Label Studio - defining project configuration needs, workflow designs, pre-labeling pipeline requirements, and integration points with ML infrastructure. Partner with the data engineering team that builds and maintains the platform.
  • Cross-functional partnership: Work with ML engineers, data scientists, and product managers to translate model requirements into well-structured labeling tasks. Challenge teams on task design when labeling instructions are ambiguous or likely to produce unreliable labels.
  • Vendor management: Source, onboard, and manage external labeling vendors and BPOs in coordination with Coalition's operations team. Set quality SLAs, run calibration sessions, and manage feedback loops to labelers. Hold vendors accountable to accuracy, not just throughput.
  • Measurement & improvement: Define and track operational metrics - label accuracy, IAA scores, cost per label, turnaround time - and use them to drive continuous improvement. Identify opportunities for active learning, model-assisted labeling, and pre-annotation to reduce cost without sacrificing quality.
Skills and Qualifications
  • 5+ years in ML data operations, data labeling, or a related field (ML engineering, data science, or data engineering with heavy labeling exposure)
  • Deep understanding of annotation quality frameworks: IAA, consensus labeling, gold standard evaluation, error taxonomy, and calibration workflows
  • Direct experience managing labeling platforms (Label Studio strongly preferred; Scale AI, Labelbox, Prodigy, or similar acceptable)
  • Track record managing outsourced labeling vendors or BPOs for ML data production
  • Familiarity with common ML labeling tasks: text classification, NER, document extraction, intent detection
  • Comfortable working in Python and SQL; bonus if you've built tooling around labeling workflows or quality measurement
  • Strong opinions on what makes labeled data good or bad, and the willingness to push back when it's bad
  • Experience in insurance, cybersecurity, or fintech is a plus but not required
Compensation

Our compensation reflects the cost of labor across several US geographic markets. The US base salary for this position ranges from $134,400/year in our lowest geographic market up to $200,000/year in our highest geographic market. Consistent with applicable laws, an employee's pay within this range is based on a number of factors, which include but are not limited to relevant education, skills, job-related knowledge, qualifications, work experience, credentials, and/or geographic location. Your recruiter can share more on target salary for your location during the interview process. Coalition, Inc. reserves the right to modify this range as needed.

Perks
  • 100% medical, dental and vision coverage
  • Flexible PTO policy
  • Annual home office stipend and WeWork access
  • Mental & physical health wellness programs (One Medical, Headspace, Wellhub, and more)!
  • Competitive compensation and opportunity for advancement