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Remote Clinical Data Abstractor Jobs in Indiana (NOW HIRING)

micro1 AI

Bioinformatics Software Engineer

Fishers, IN · Remote

$80 - $110/hr

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

Milliman

Strategic Data Partnership Manager

Indianapolis, IN · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... how to unlock -- claims, clinical, social determinants, lab, Rx, mortality, pricing. The ... This position is fully remote, while occasional travel may be required. Primary Responsibilities:

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All JobsClinical Data Abstractor JobsRemote Clinical Data Abstractor JobsRemote Clinical Data Abstractor Jobs in Indiana

Remote Clinical Data Abstractor information

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

As of Aug 14, 2026, the average hourly pay for remote clinical data abstractor in Indiana is $24.10, according to ZipRecruiter salary data. Most workers in this role earn between $17.60 and $30.43 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 Indiana?

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

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

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

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

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

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

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

Remote Clinical Data Abstractor jobs near you
Infographic showing various Remote Clinical Data Abstractor job openings in Indiana as of August 2026, with employment types broken down into 2% As Needed, 85% Full Time, 9% Part Time, and 4% Contract. Highlights an 100% Remote job distribution, with an average salary of $50,135 per year, or $24.1 per hour.

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Fishers, IN • Remote

$80 - $110/hr

Part-time

Posted 11 days ago

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.

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