Note: The job is a remote job and is open to candidates in USA. The client designs and manufactures robot-assisted systems for minimally invasive surgery, using technology to improve surgical efficacy and patient safety. The Clinical Data Specialist will develop, review, and maintain clinical ground truth datasets from surgical videos, images, and clinical information to support AI/ML research, product development, and verification and validation. The role also involves clinical annotation, quality review, discrepancy investigation, documentation, and collaboration with technical, clinical, quality, and regulatory stakeholders.
Responsibilities
- Review annotations produced by human annotators, clinical experts, external providers, and AI/ML models to ensure accuracy and consistency
- Identify, document, and escalate ambiguous cases, annotation discrepancies, and data-quality risks for clinical review or adjudication
- Participate in annotation training, calibration, qualification, and inter-annotator agreement activities
- Maintain annotation guidelines, quality criteria, review decisions, dataset changes, and other supporting documentation
- Support traceability between source data, annotation versions, quality reviews, adjudication decisions, and approved dataset outputs
- Collaborate with engineers, researchers, surgeons, clinical experts, and external providers to translate clinical data requirements into annotation and review activities
- Contribute to clinical data collection, tool and model evaluation, and workflow improvements that increase efficiency while maintaining clinical accuracy and data quality
- Conduct clinical research through literature review, procedural analysis, and consultation with clinical experts to support AI/ML research and product-development needs
Skills
- Bachelor's degree in biology, physiology, biomedical engineering, nursing, clinical sciences, health sciences, or a related field
- Strong understanding of human anatomy and an interest in learning surgical procedures across multiple specialties
- Experience interpreting medical images, surgical videos, clinical workflows, or other complex visual data
- Experience with data annotation, clinical data review, medical research, clinical operations, or a related field
- Ability to learn and use specialized annotation platforms, data-management systems, and project-tracking tools
- Strong analytical and problem-solving skills, including the ability to recognize patterns, inconsistencies, and potential data-quality risks
- Demonstrated ability to follow detailed clinical definitions and apply them consistently
- Excellent documentation skills and the ability to clearly explain annotation decisions and clinical reasoning
- Ability to handle confidential, proprietary, and sensitive clinical information professionally
- Excellent attention to detail and commitment to clinical accuracy and data quality
- Strong written and verbal communication skills, including clear documentation of decisions and concerns
- Ability to collaborate effectively with clinical, technical, operational, and quality-focused stakeholders
- Sound judgment regarding when to make an independent decision and when to escalate a clinical or quality concern
- Ability to translate clinical and AI/ML research objectives into practical data collection, annotation, and quality-review guidelines
- Ability to manage multiple projects, priorities, and deadlines in a fast-paced environment
- Proactive and transparent in communicating mistakes, uncertainty, risks, and process challenges
- Ability to work independently while remaining closely coordinated with a cross-functional team
- Open to giving and receiving constructive feedback and contributing to continuous improvement
Benefits
- Remote work arrangement
Company Overview
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