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Remote Clinical Data Abstractor Jobs in Virginia

Clinical Trial Psych Rater

Fairfax, VA · Remote

$62K - $156K/yr

Remote/Virtual Hours: Estimated 10-16 hours per month Role: Clinical Specialist About IQVIA IQVIA ... Review case data and prepare for rater discussions, ensuring all relevant documents and scale items ...

Authorization Coordinator

Norfolk, VA · On-site +1

$18 - $22.25/hr

... other Clinical providers ensuring clinical data is substantial enough to authorize services ... For positions that are available as remote work, Sentara Health employs associates in the following ...

Monday to Friday flexible schedule with 1-day/week remote work available. Weekend coverage 6-7 ... Evaluates and tracks data for outcomes and related performance improvement measures and makes ...

IT HEDIS & Analytics Manager

Norfolk, VA · On-site +1

$29.25 - $38.75/hr

Knowledge of ECDS, digital HEDIS measures, FHIR, HIE integration, and clinical-data exchange ... For positions that are available as remote work, Sentara Health employs associates in the following ...

Showing results 41-60

Remote Clinical Data Abstractor information

See Virginia salary details

$14

$25

$38

How much do remote clinical data abstractor jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for remote clinical data abstractor in Virginia is $25.11, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $31.68 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote clinical data abstractor?

To excel as a Remote Clinical Data Abstractor, you need a strong background in medical terminology, anatomy, and clinical documentation, often supported by experience in healthcare or a related degree. Familiarity with electronic health record (EHR) systems, data abstraction software, and certifications such as RHIA, RHIT, or CCS are highly valued. Attention to detail, self-motivation, and strong communication skills are essential soft skills in this remote role. These competencies ensure accurate extraction and management of clinical data, supporting compliance and quality improvement initiatives.

What are some common challenges faced by remote clinical data abstractors, and how can they be managed?

Remote Clinical Data Abstractors often encounter challenges such as managing large volumes of complex medical records, interpreting varied documentation styles, and maintaining accuracy under tight deadlines. Staying organized through effective time management and utilizing standardized abstraction guidelines can help mitigate these obstacles. Regular communication with clinical teams and ongoing training are also important for resolving ambiguities and staying updated on best practices. Adapting to a remote environment requires self-discipline, but with the right tools and support, most abstractors can excel and find satisfaction in the vital work they do.

What are the most commonly searched types of Clinical Data Abstractor jobs in Virginia?

The most popular types of Clinical Data Abstractor jobs in Virginia are:

What are popular job titles related to Remote Clinical Data Abstractor jobs in Virginia?

For Remote Clinical Data Abstractor jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Clinical Data Abstractor jobs in Virginia look for?

The top searched job categories for Remote Clinical Data Abstractor jobs in Virginia are:

What cities in Virginia are hiring for Remote Clinical Data Abstractor jobs?

Cities in Virginia with the most Remote Clinical Data Abstractor job openings:

Infographic showing various Remote Clinical Data Abstractor job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $52,235 per year, or $25.1 per hour.

AI Training Specialist - Cheminformatics

micro1 AI

Roanoke, VA • Remote

$80 - $110/hr

Part-time

This job post has expired today. Applications are no longer accepted.


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.