Clinical Data Specialist

Intuitive•Sunnyvale, CA

About The Position

Intuitive is seeking a Clinical Data Specialist to support the development and validation of artificial intelligence and machine learning technologies for robotic-assisted surgery. The role creates, reviews, and maintains high-quality clinical ground-truth datasets derived from surgical videos, images, and related clinical information, translating clinical and technical requirements into accurate, consistent, and traceable data. The specialist performs clinical annotation and quality review, investigates discrepancies, maintains dataset and methodology documentation, and supports dataset preparation for machine-learning research, product development, and verification and validation activities. The role collaborates with machine-learning engineers, researchers, surgeons, clinical experts, quality and regulatory partners, data operations teams, and external annotation providers. It calls for knowledge of anatomy and surgical workflows, careful documentation, and sound judgment when handling complex or ambiguous clinical data.

Requirements

Bachelor’s degree in biology, physiology, biomedical engineering, nursing, clinical sciences, health sciences, or a related field.
Strong understanding of human anatomy and 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 recognizing patterns, inconsistencies, and potential data-quality risks.
Ability to follow detailed clinical definitions and apply them consistently.
Excellent documentation skills and 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 about 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 communication about mistakes, uncertainty, risks, and process challenges.
Ability to work independently while remaining closely coordinated with a cross-functional team.
Openness to giving and receiving constructive feedback and contributing to continuous improvement.

Responsibilities

Review annotations created by human annotators, clinical experts, external providers, and AI/ML models for 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 supporting documentation.
Support traceability across 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 preserve clinical accuracy and data quality.
Conduct clinical research, including literature review, procedural analysis, and consultation with clinical experts, to support AI/ML research and product-development needs.