Does this employer sponsor visas?
Source: US DOL Office of Foreign Labor Certification, LCA disclosure data, FY2026 Q2. Government data is published roughly one quarter in arrears.
No single filed job title matched this advert closely enough, so the figure above is Intuitive Surgical Operations, Inc.’s median across every role it sponsored.
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The role, as Intuitive Surgical Operations, Inc. describes it
Fluorescence Imaging at Intuitive Surgical The Fluorescence Imaging Team at Intuitive is developing agents designed to work seamlessly with Intuitive's robotic platforms and Firefly imaging technology. The agents have the potential to highlight critical anatomy and disease in real time—giving surgeons clearer information at the moment decisions matter most and helping improve outcomes for patients. Primary Function of Position The Senior Clinical Scientist is responsible for supporting 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 the generation of evidence used to evaluate imaging agents, software tools, and future ecosystem applications. The position serves as a bridge between clinical development, data science, engineering, and external partners, helping ensure that scientific questions are translated into clinically meaningful, measurable, and regulatory-defensible outcomes. The successful candidate will combine expertise in clinical research methodology with a strong understanding of diagnostic performance assessment, clinical data interpretation, and evidence generation in support of innovative surgical technologies. Roles and Responsibilities Clinical Study Design and Endpoint Development - Support execution of clinical studies evaluating fluorescence imaging agents and ecosystem technologies. - Translate protocol-defined endpoints into operationally executable study procedures and data collection requirements. - Partner with Clinical Development, Data Management, and Biostatistics to ensure endpoint assessments are implemented consistently across sites. - Develop study-specific guidance supporting accurate and reproducible endpoint determination. - Support review of protocols and statistical analysis plans to ensure alignment between study procedures, data collection methods, and endpoint assessments. - Conduct literature reviews and scientific assessments supporting ongoing clinical development activities. Clinical Data Collection & Quality Strategy - Develop data collection frameworks supporting assessment of imaging performance and clinical outcomes. - Partner with Data Management to design CRFs, edit checks, and data review workflows. - Define procedures for collection of imaging, pathology, surgical, and clinical outcome data. - Establish data quality metrics and review processes to 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 throughout study conduct. Data Monitoring and Evidence Generation - Develop risk-based data monitoring and data review approaches for fluorescence imaging programs. - Conduct scientific review of 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 development of evidence packages supporting clinical, scientific, and business objectives. AI & Data Science Collaboration - Partner with Data Science and Engineering teams to develop high-quality datasets supporting 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 to support future computational and ecosystem initiatives. - Contribute to evidence-generation activities supporting AI-enabled
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