Sr Clinical Imaging Scientist

Intuitive•Sunnyvale, CA

1d•$132,000 - $223,500•Onsite

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 robust clinical endpoints, defining data collection strategies, establishing data quality and monitoring processes, and supporting evidence generation to evaluate imaging agents, software tools, and future ecosystem applications. This position bridges clinical development, data science, engineering, and external partners to translate scientific questions into clinically meaningful, measurable, and regulatory-defensible outcomes. The successful candidate applies clinical research methodology and expertise in diagnostic performance assessment, clinical data interpretation, and evidence generation for innovative surgical technologies.

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 implement endpoint assessments consistently across sites.
Develop study-specific guidance for accurate and reproducible endpoint determination.
Review protocols and statistical analysis plans for alignment among study procedures, data collection methods, and endpoint assessments.
Conduct literature reviews and scientific assessments supporting clinical development.
Develop data collection frameworks for assessing 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 that promote completeness, consistency, and protocol compliance.
Identify potential sources of variability, bias, and missing data and recommend mitigation strategies.
Support ongoing review of clinical data during study conduct.
Develop risk-based data monitoring and data 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 on interpretation of 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 established clinical endpoints and reference standards.
Provide clinical and workflow expertise for future computational and ecosystem initiatives.
Contribute to evidence-generation activities 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 consistency of endpoint definitions and scientific rationale across development documents.