Staff Epidemiologist- Future Forward

Company Description

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.

We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.

If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.

Job Description

The Staff Epidemiologist, Real-World Evidence Generation will design and execute data-driven
analyses using claims databases and real-world evidence to demonstrate the clinical and economic
value of emerging robotic platforms. This role focuses on rigorous statistical analysis of U.S.
commercial and Medicare claims data, real-world outcomes research, and translating findings into
evidence that supports regulatory submissions, payer discussions, and clinical adoption. The
successful candidate will combine epidemiologic expertise with advanced statistical methods to
generate peer-reviewed publications and evidence dossiers that demonstrate procedure value and
patient benefit.
Essential Job Duties
 Real-World Evidence Generation & Claims Data Analysis
 Design and execute comprehensive analyses using U.S. commercial claims databases
(e.g., MarketScan, Optum), Medicare data, and other population-level observational
datasets to evaluate procedure outcomes, safety, and resource utilization.
 Develop and apply rigorous epidemiologic and statistical methods (descriptive, analytic,
causal inference techniques) to real-world data to characterize patient populations, identify
responder phenotypes, and quantify procedure value.
 Build and document complex research datasets by integrating multi-source claims data
(medical, pharmaceutical, facility claims) with appropriate data governance and quality
assurance protocols.
 Conduct comparative effectiveness research, cost analysis, and health outcomes
assessment using claims-based methodologies.
 Ensure compliance with data use agreements, privacy regulations, and analytical standards
in all database projects.
Statistical Analysis & Methodology
 Perform advanced statistical analyses including logistic regression, survival analysis,
propensity score matching, instrumental variable analysis, and other causal inference
methods appropriate for observational data.
 Develop and document standardized analytical code libraries (SAS, R, SQL) that enable
reproducible, transparent research and support collaboration across teams.
 Apply epidemiologic principles to address confounding, selection bias, and other threats to
validity in observational research.
 Interpret complex statistical findings and communicate results clearly to both technical and
non-technical audiences.

Health Economics Integration
 Support health economic analyses by providing clinical outcome data, cost drivers, and
utilization patterns derived from claims databases.
 Partner with HEOR colleagues to integrate real-world evidence with economic models,
ensuring clinical parameters reflect actual patient populations and healthcare system
utilization.
 Quantify resource utilization, cost burden, and clinical benefits for target patient populations
using claims-based metrics.
 Contribute epidemiologic and statistical expertise to develop value propositions grounded in
evidence.
Evidence Translation, Publication Strategy & External Scientific Engagement
 Lead peer-reviewed publication development for real-world evidence studies, ensuring
methodologic rigor and clinical relevance.
�� Translate research findings into clear, evidence-based value dossiers and briefing
documents for regulatory, payer, and clinical stakeholders.
 Communicate complex methodologic approaches and findings to diverse audiences
through publications, regulatory submissions, and scientific presentations.
 Collaborate with cross-functional teams to align evidence generation with r