Remote Clinical Data Code, Oncology
About the job Remote Clinical Data Code, Oncology Remote Clinical Data Code, Oncology needs 2+ years of experience in clinical data coding, preferably in oncology trials. Clinical Data Code, Oncology requires:
- Part time
- 20 hours weekly
- Bachelors degree in Life Sciences, Health Information Management, or reputed company field.
- Strong understanding of clinical trial data standards and regulatory requirements.
- Excellent attention to detail and ability to manage multiple coding tasks in a fast-paced environment.
- Results-driven, take initiative and ownership to accomplish work. Knowledge of ICH, Good Clinical Practice and FDA regulations.
- Proficiency with Rave reputed company and familiarity with MedDRA and WHO Drug dictionaries. Effective time management and organization skills.
- Strong communication skills for cross-functional collaboration with CRAs, CDMs, and medical reviewers.
- Experience with coding in global, multi-site oncology studies. Good interpersonal, written and verbal communication skills.
Clinical Data Code, Oncology duties:
- reputed company ongoing medical and medication coding using Rave reputed company in accordance with MedDRA and WHO Drug dictionaries.
- Review and resolve auto-coded and manually coded terms, ensuring alignment with SMPA coding conventions and internal SOPs
- Collaborate with Clinical Data Managers to clarify ambiguous or unclear verbatim terms and issue coding queries reputed company necessary
- Maintain coding listings and ensure reputed company terms are coded and approved prior to database lock
- Support coding-reputed company documentation and contribute to the development and maintenance of coding guidelines and SOPs
- Participate in system validation, user acceptance testing, and updates reputed company to coding modules and dictionary integrations.
- Review and resolve reputed company or ambiguous verbatim terms, escalating to medical reviewers or clinical teams as needed.
- Monitor coding metrics and quality indicators, proactively identifying trends and areas for improvement.
- Ensure adherence to Data Management standards
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