Sr Clinical Imaging Scientist

Intuitive•Sunnyvale, CA

10h

About The Position

The Senior Clinical Scientist supports the scientific design and execution of clinical evidence-generation activities across Intuitive’s fluorescence imaging ecosystem. The role focuses on developing clinical endpoints, defining data collection strategies, establishing data quality and monitoring processes, and generating evidence to evaluate imaging agents, software tools, and future ecosystem applications. It bridges clinical development, data science, engineering, and external partners to translate scientific questions into clinically meaningful, measurable, and regulatory-defensible outcomes. The role supports clinical studies of fluorescence imaging agents and ecosystem technologies; develops operational guidance for endpoint assessment and data collection; and collaborates with Clinical Development, Data Management, and Biostatistics. It also contributes to scientific data review, evidence packages, AI-enabled imaging datasets and validation, regulatory materials, publications, and scientific communications.

Requirements

PhD, PharmD, MD, MPH, or MS in biomedical sciences, clinical research, epidemiology, biomedical engineering, or a related field.
At least 5 years of experience in clinical research, clinical development, medical affairs, diagnostics, medical devices, pharmaceuticals, or related healthcare industries.
Experience supporting clinical study design and endpoint development.
Strong understanding of clinical research methodology and evidence generation.
Experience interpreting clinical and diagnostic performance data.
Familiarity with protocol development, clinical databases, and data review processes.
Ability to work effectively across multidisciplinary teams.
Strong scientific writing, presentation, and communication skills.

Nice To Haves

Experience in oncology, surgical oncology, medical imaging, molecular imaging, or fluorescence-guided surgery.
Experience supporting regulatory submissions or health authority interactions.
Familiarity with diagnostic accuracy studies, including sensitivity, specificity, predictive values, and reference-standard methodology.
Experience working with imaging datasets, digital pathology, AI/machine learning applications, or quantitative image analysis.
Experience collaborating with software, data science, or engineering teams.
Knowledge of robotic-assisted surgery and image-guided procedures.

Responsibilities

Support execution of clinical studies evaluating fluorescence imaging agents and ecosystem technologies.
Translate protocol-defined endpoints into executable study procedures and data collection requirements.
Partner with Clinical Development, Data Management, and Biostatistics to support consistent endpoint assessments across sites.
Develop study-specific guidance for accurate and reproducible endpoint determination.
Review protocols and statistical analysis plans for alignment among procedures, data collection, and endpoint assessments.
Conduct literature reviews and scientific assessments for clinical development activities.
Develop data collection frameworks for evaluating imaging performance and clinical outcomes.
Partner with Data Management to design case report forms, edit checks, and data review workflows.
Define procedures for collecting imaging, pathology, surgical, and clinical outcome data.
Establish data quality metrics and review processes to promote completeness, consistency, and protocol compliance.
Identify potential variability, bias, and missing-data sources and recommend mitigation strategies.
Support ongoing clinical data review during study conduct.
Develop risk-based data monitoring and review approaches for fluorescence imaging programs.
Scientifically review emerging study data and identify trends requiring further investigation.
Support blinded image review workflows and centralized assessment activities.
Collaborate with Clinical Development and Biostatistics to interpret study results.
Assist with database lock activities, clinical study reports, publications, abstracts, and presentations.
Contribute to evidence packages supporting clinical, scientific, and business objectives.
Partner with Data Science and Engineering to develop high-quality datasets for AI-enabled imaging applications.
Support development of annotation strategies, reference standards, and validation datasets.
Assist in evaluating algorithm performance against clinical endpoints and reference standards.
Provide clinical and workflow expertise for computational and ecosystem initiatives.
Contribute to evidence generation for AI-enabled features and third-party ecosystem applications.
Author and review scientific content for protocols, study reports, publications, and internal development documents.
Support preparation of materials for regulatory interactions and health authority submissions.
Present scientific findings to internal stakeholders and external collaborators.
Maintain consistent endpoint definitions and scientific rationale across development documents.