Senior Clinical Data Scientist

Intuitive•Sunnyvale, CA

About The Position

The Senior Clinical Data Scientist will work within Intuitive’s Ion business unit, supporting the Ion endoluminal robotic system for minimally invasive peripheral lung biopsy. The role bridges clinical science and data science, translating clinical questions into rigorous analyses that inform product strategy, evidence generation, and business decisions. The position reports to the Managing Staff, Clinical Data Science. The scientist will collaborate with clinicians, internal and external stakeholders, cross-functional teams, and data engineering to define hypotheses grounded in customer needs, identify suitable data sources, conduct quantitative analyses, and communicate findings that advance patient outcomes and business objectives. The role combines clinical understanding of the Ion platform with practical expertise in Python or R, statistics, and causal reasoning, along with the ability to work through ambiguity and clearly communicate complex results. The position contributes to clinical and economic evidence strategies, clinical trials, and regulatory submissions. It also supports reproducible analytics through organized, documented codebases and promotes data-informed decision-making across the organization.

Requirements

At least 6 years of experience with a master’s degree, or at least 4 years with a PhD, in a quantitative, scientific, or engineering field such as biostatistics, epidemiology, data science, computer science, biomedical engineering, public health, or a related discipline; an MD with quantitative research experience is also 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 or registry data, and claims or EHR-style databases.
Experience with 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 data visualization tools such as Tableau to present complex data to non-technical stakeholders or regulatory bodies.
Experience with Electronic Data Capture systems such as Medrio for managing clinical study or registry data.
Experience using AI/ML tools to accelerate software development and data analysis workflows.

Nice To Haves

Strong critical thinking and analytical skills, including framing ambiguous clinical questions as testable hypotheses and selecting fit-for-purpose methods.
Excellent organization, especially in code management and documentation.
Ability to work effectively with cross-functional teams, including clinicians, engineers, regulatory, commercial, and data science partners.
Self-starter who can manage multiple priorities, work independently, and deliver amid ambiguity.
Track record of 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 such as HIPAA and GDPR.
Familiarity with the lung cancer landscape, including screening, diagnosis, and treatment.

Responsibilities

Identify data-centric clinical needs with internal and external stakeholders, including clinicians, administrators, and policymakers, and translate them into prioritized research questions and testable hypotheses.
Design, implement, and validate quantitative analyses in Python or R using appropriate statistical, machine learning, and causal inference methods.
Analyze Ion device logs, clinical study and registry data, insurance claims databases, and EHR/EMR data.
Translate analyses into decision-useful narratives tailored to technical peers, senior leadership, and external physicians.
Demonstrate the impact of analyses through reports, presentations, dashboards, peer-reviewed publications, and customer-facing deliverables.
Partner with cross-functional teams to design and execute global clinical and economic evidence strategies, including designing and supporting clinical trials.
Support regulatory submissions by structuring and validating clinical datasets for FDA and EU MDR compliance standards.
Create and maintain reproducible codebases with clear documentation, version control, and consistent coding standards.
Champion data use and evidence generation to support product improvement and a data-driven culture.