Overview
Remote
Depends on Experience
Contract - W2
Contract - 6 Month(s)
No Travel Required
Skills
CAP Pathology Report
LIMS
REDCap
Epic Beaker
Job Details
Looking for an experienced Pathology Assistant to work closely with our AI technical team in developing automation tools for reading and extracting data from CAP-formatted pathology reports. Your role will be critical in guiding the AI s understanding of pathology language, structures, and staging logic especially for cancer reports following AJCC guidelines.
This is a fully remote, part-time contract position with flexible hours.
Key Responsibilities:
Read and interpret pathology reports in various formats that follow the College of American Pathologists (CAP) templates.
Collaborate with the AI/ML engineering team to:
Identify and annotate key data elements in reports (e.g., tumor type, size, margins, staging).
Train models to recognize structured fields from free-text.
Provide validation and feedback on data extracted by the AI.
Assist in mapping pathological findings to dropdown-based data entry formats.
Review and QA processed reports, flagging any inconsistencies or gaps in interpretation.
Support the development of a confidence scoring framework for automated entries.
Help maintain clinical accuracy of a pathology-specific knowledge base used by AI.
Ideal Candidate Has:
3+ years of experience working with CAP pathology reports, either in a clinical, research, or pathology lab setting.
Strong familiarity with AJCC staging systems, terminology, and variations across tumor types.
Hands-on experience with digital pathology or structured data entry is a big plus.
Clear communication skills and ability to work cross-functionally with engineers and non-clinical teams.
Detail-oriented mindset with a strong sense of clinical accuracy.
Comfort working remotely and using collaborative tools (Zoom, Google Docs, Slack, etc.)
Preferred Qualifications:
Degree or certification in Pathology Assisting, Histotechnology, Biomedical Sciences, or similar field.
Prior experience in clinical informatics, health data annotation, or AI/ML teams.
This is a fully remote, part-time contract position with flexible hours.
Key Responsibilities:
Read and interpret pathology reports in various formats that follow the College of American Pathologists (CAP) templates.
Collaborate with the AI/ML engineering team to:
Identify and annotate key data elements in reports (e.g., tumor type, size, margins, staging).
Train models to recognize structured fields from free-text.
Provide validation and feedback on data extracted by the AI.
Assist in mapping pathological findings to dropdown-based data entry formats.
Review and QA processed reports, flagging any inconsistencies or gaps in interpretation.
Support the development of a confidence scoring framework for automated entries.
Help maintain clinical accuracy of a pathology-specific knowledge base used by AI.
Ideal Candidate Has:
3+ years of experience working with CAP pathology reports, either in a clinical, research, or pathology lab setting.
Strong familiarity with AJCC staging systems, terminology, and variations across tumor types.
Hands-on experience with digital pathology or structured data entry is a big plus.
Clear communication skills and ability to work cross-functionally with engineers and non-clinical teams.
Detail-oriented mindset with a strong sense of clinical accuracy.
Comfort working remotely and using collaborative tools (Zoom, Google Docs, Slack, etc.)
Preferred Qualifications:
Degree or certification in Pathology Assisting, Histotechnology, Biomedical Sciences, or similar field.
Prior experience in clinical informatics, health data annotation, or AI/ML teams.
Familiarity with tools like REDCap, Epic Beaker, or LIMS systems is a bonus.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.