# Sr Clin Data Abstractor Temp to Hire at Natera

- Company: Natera
- What the company does: Dedicated to oncology, women’s health, and organ health. Natera’s cell-free DNA tests help protect health and inform more personalized decisions about care. Backed by Lightspeed and Sequoia.
- Company website: https://natera.com/
- Type: Startups
- Level: Senior
- Location: US Remote
- Work setup: Remote
- Posted: 2026-09-25
- Apply by: 2026-11-09
- Apply: https://job-boards.greenhouse.io/natera/jobs/6208401004
- Page: https://www.1752.vc/careers/jobs/natera-sr-clin-data-abstractor-temp-to-hire/

## About the role

Perform high-quality medical record abstraction by combining proficient-level experiences in data management and software with medical terminology, medical coding, information encoding, and analytical capabilities. Interpret and manage complex clinical patient data for research, quality improvement, and regulatory reporting.

## What they're looking for

- Clinical Background: U. S. licensed Nurse, PA-C, NP, or DNP is required with a Master’s degree in health sciences. Strong understanding of medical terminology, disease processes (especially cancer), standard clinical workflows, and genetic testing
- Clinical Experience: Minimum of 4-5 years of experience in clinical data abstraction and medical records review, preferably in cancer, women’s health, rare diseases
- Data Abstraction Expertise: Proven ability to accurately read, interpret, and abstract complex clinical information from various electronic and paper medical record sources
- Data Management Expertise: Direct experience performing clinical data encoding using standard ontologies including but not limited to ICD-10-CM and SNOMED CT. Direct experience performing data mapping, standardization, and harmonization
- Quality and Compliance: Demonstrated commitment to data integrity, quality control processes, and adherence to HIPAA and other data privacy regulations
- Certifications/Industry Expertise: CCDM, CCRP, ACR-P, or CRA preferred

Tags: Clinical Genomics