Clinical Data Labelling Specialist Oncology

Cliniminds

4 - 5 years

8 - 12 Lacs

Mumbai

Posted:1 month ago| Platform:

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Skills Required

Oncology Data Clinical Data Labelling Specialist Oncology ICD- 10 ICD-O-3 Oncology oncology data abstraction RxNorm medications clinical research workflows dataset quality control Data Labelling data harmonization genetic variant notation HGVS audit trails

Work Mode

Work from Office

Job Type

Full Time

Job Description

Clinical

Key Responsibilities:

Review and label clinical oncology data from medical records, pathology reports, radiology findings, and molecular/genomic profiles.
Ensure consistency, accuracy, and completeness in annotation across datasets used for model training and clinical validation.
Apply standardized medical coding systems such as
ICD-10,

ICD-O-3, RxNorm, and HGVS
for labeling and data harmonization.
Work closely with medical reviewers, data engineers, and AI teams to refine labeling schemes and contribute to dataset quality control.
Document and manage audit trails of labeling activities and highlight inconsistencies or data quality issues.
Support ongoing data abstraction tasks for internal research and external oncology projects.

Required Qualifications:

Bachelors or Masters degree in
Biosciences
, Biotechnology, Life Sciences, or a related healthcare discipline.
Familiarity with medical terminologies, particularly in
oncology
and related clinical domains.
Ability to interpret unstructured clinical text and identify key data points (diagnosis, histology, tumor site, biomarkers, etc.).

Preferred Qualifications:

Experience in
oncology data abstraction
, working with clinical trials, cancer registries, or data management teams.
Working knowledge and practical application of coding standards such as
ICD- 10, ICD-O-3 (Oncology), RxNorm (medications), and HGVS (genetic variant notation)
.
Knowledge of clinical research workflows.

Key Skills:

Strong attention to detail and commitment to data accuracy.
Analytical mindset with the ability to interpret complex clinical data.
Effective communication and teamwork in a fast-paced development environment.
Proficient in using Excel.

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