Senior Clinical Data Scientist

The Senior Clinical Data Scientist will join the Ion business unit at Intuitive Surgical, translating clinical questions into rigorous, data-driven analyses. The work supports product strategy, evidence generation, and business decision-making by combining clinical science with advanced analytics.

Role Overview

In this onsite role in Sunnyvale, CA, the Senior Clinical Data Scientist partners with clinical and business stakeholders to identify data needs and shape them into prioritized research questions with testable hypotheses. Analyses will be applied across device logs, clinical studies and registries, insurance claims databases, and EHR/EMR data, with results communicated to technical peers, senior leadership, and external physicians.

Key Responsibilities

• Collaborate with internal and external stakeholders, including clinicians, administrators, and policymakers, to identify clinical data needs and translate them into prioritized research questions with testable hypotheses.
• Design, implement, and validate quantitative analyses in Python or R, applying statistical, machine learning, and causal inference methods to test hypotheses using Ion device logs, clinical studies/registries, insurance claims, and EHR/EMR data.
• Turn analysis findings into decision-useful narratives tailored to multiple audiences, including technical teams, senior leaders, and external physicians focused on efficiency improvements.
• Demonstrate impact through internal and external reporting, presentations, dashboards, peer-reviewed publications, and customer-facing deliverables.
• Partner with cross-functional teams to support global clinical and economic evidence strategies, including designing and supporting clinical trials.
• Support regulatory submissions by structuring and validating clinical datasets aligned to FDA and EU MDR compliance standards.
• Create and maintain organized, reproducible codebases with clear documentation, version control, and consistent coding standards.
• Champion data-driven culture internally to generate evidence that supports building a better product.

Required Qualifications

• 6+ years of experience with a Master's degree or 4+ years of experience with a PhD in a quantitative, scientific, or engineering field (e.g., biostatistics, epidemiology, data science, computer science, biomedical engineering, public health, or related disciplines).
• MD with quantitative research experience accepted.
• Experience using Python or R for data analysis, statistical modeling, and visualization.
• Working knowledge of SQL for querying and managing structured datasets.
• Demonstrated experience with causal inference methods and study design.
• Experience working with device-generated log data, clinical study/registry data, and claims/EHR-style databases.
• Experience applying causal inference in a healthcare or medical device context.
• Experience using platforms such as Snowflake or Databricks for production-level data pipelines and analytics.
• Experience with Tableau or similar tools for presenting complex data to non-technical stakeholders or regulatory bodies.
• Experience with Electronic Data Capture (EDC) systems (e.g., Medrio) for managing clinical study/registry data.
• Experience using AI/ML tools to accelerate software development and data analysis workflows.

Preferred Skills and Experience

• Strong critical thinking and analytical skills, including the ability to frame ambiguous clinical questions as testable hypotheses and select appropriate methods.
• Strong organization skills, especially around code management and documentation.
• Ability to collaborate across functions, including clinicians, engineers, regulatory, commercial, and data science partners.
• Self-starter mindset with capability to manage multiple priorities, operate independently, and deliver under ambiguity.
• Peer-reviewed publications or conference presentations in clinical research or data science.
• Experience in medical devices or other regulated industries.
• Familiarity with Good Clinical Practice (GCP), ISO 14155, and data privacy regulations (HIPAA/GDPR).
• Familiarity with the lung cancer landscape (screening, diagnosis, treatment).

Technologies

• Python
• R
• SQL
• Snowflake
• Databricks
• Tableau
• Electronic Data Capture (EDC) systems
• Medrio
• AI/ML tools

Location, Schedule, and Compensation

• Location: Sunnyvale, CA, United States (onsite)
• Shift: Day
• Workplace type: Purposeful Onsite, requiring onsite presence for leader-defined events and activities, which could be monthly or annually; onsite frequency may increase based on business need.
• Salary: USD 152,000 to 257,200 per year
• Base compensation ranges: Region 1: $178,800 to $257,200; Region 2: $152,000 to $218,600

Additional Information

• Due to the nature of the business and the role, Intuitive and/or its customer(s) may require proof of current vaccination against certain diseases, including COVID-19.
• Intuitive is an Equal Opportunity Employer.
• U.S. Export Controls Disclaimer: certain roles may be subject to U.S. export controls for prospective employees who are nationals from countries on embargo or sanctions status. For export-control subject roles, final offers depend on obtaining an approved export license and/or executing a TCP before the candidate’s start date.
• Qualified applicants with arrest and conviction records will be considered in accordance with fair chance laws.
• Preference may be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.
• This position may be filled at a different job level based on business need and/or the selected candidate’s experience, knowledge, and skills.
• Compensation will be based primarily on the job level at which the role is filled and the candidate’s qualifications, consistent with applicable law.
• Accommodation & Accessibility Notice: contact People Services at [email protected] for assistance or an accommodation during the application or interview process.