Remote Oncology Data Abstractor III

Remote; San Francisco (CA); Remote; USD 39,000 - 47,000; Full time

Benefits offered by this job

Equity at hire

Discretionary annual bonus

401K plan

Job summary

N-Power Medicine is seeking a Clinical Data Abstractor III to curate oncology datasets from multiple EHR systems into our EDC. You will ensure quality, comply with GCP, SOPs, and HIPAA, and collaborate with QA and biostatistics to resolve data issues.

The role is remote within the United States, with 90-100% effort on abstraction and opportunities to contribute to platform development and pre-screening efforts. 3+ years of oncology data abstraction required.

Qualifications

• 3+ years of oncology data abstraction experience.
• Experience navigating EHR/EMR systems (Epic, Cerner, OncoEMR, Iknowmed).
• Familiarity with oncology clinical trial eligibility criteria and protocol review.
• Familiarity with genomic testing in cancer is preferred.

Responsibilities

• Retrieve, abstract and curate oncology data from EHR platforms into NPM or 3rd party EDC.
• Conduct pre-screening chart reviews to assess patient eligibility against protocol criteria.
• Maintain pre-screening logs and dashboards to document eligibility status.
• Ensure compliance with SOPs, GCP, and HIPAA requirements.
• Contribute to process improvements for abstraction workflows and UI/UX.
• Collaborate with quality management and biostatistics to resolve data issues.

Skills

Oncology data abstraction

EHR navigation

HIPAA compliance

Data quality

Team collaboration

Communication skills

Education

RN/LPN

CRA certification

Tools

Epic

Cerner

OncoEMR

Iknowmed

Job description

N-Power Medicine is seeking a Clinical Data Abstractor III to curate oncology datasets from multiple EHR systems into our EDC. You will ensure quality, comply with GCP, SOPs, and HIPAA, and collaborate with QA and biostatistics to resolve data issues.

The role is remote within the United States, with 90-100% effort on abstraction and opportunities to contribute to platform development and pre-screening efforts. 3+ years of oncology data abstraction required.