Senior Epidemiologist- Future Forward

Intuitive•Sunnyvale, CA

About The Position

The Senior 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.

Requirements

Advanced degree in Epidemiology, Public Health, Biostatistics, Statistics, or related quantitative field (PhD, MSc strongly preferred); MD/DO with substantial epidemiologic or clinical research background may be considered
7–10+ years of experience in epidemiologic research, real-world evidence generation, or outcomes research, with demonstrated expertise in claims database analysis
Advanced proficiency in statistical programming languages (SAS, R, SQL) and experience building and managing large, complex datasets from multiple sources
Direct experience accessing, analyzing, and interpreting U.S. commercial and Medicare claims databases (e.g., MarketScan, Optum, CMS data)
Strong knowledge of epidemiologic study designs, causal inference methods, and statistical approaches for observational data
Track record of peer-reviewed publications demonstrating methodologic rigor and clinical impact
Proven ability to work independently on complex analyses while collaborating effectively with cross-functional teams
Strong communication skills with ability to translate statistical findings for diverse stakeholder groups
Experience working in fast-paced, innovation-driven environments within medical device, biotech, or health technology sectors
Willingness to travel domestically for key engagements and meetings, as required (up to 25%)

Responsibilities

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 regulatory pathways and market access objectives.
Identify and establish relationships with key opinion leaders and clinical experts relevant to procedural outcomes and value demonstration.
Develop publication roadmaps in collaboration with identified KOLs to ensure real-world evidence reaches target clinical audiences and informs procedural adoption.
Partner with KOLs on evidence interpretation and manuscript development to strengthen methodologic rigor, clinical relevance, and impact of findings.
Lead strategic positioning of real-world evidence findings at key conferences, in high- impact peer-reviewed journals, and through clinical society engagement to build procedural credibility.
Support advisory activities and collaborative research initiatives with clinical thought leaders that align with evidence generation priorities and external validation.
Cross-Functional Collaboration
Work with Clinical Affairs, Regulatory, and Market Access teams to identify key evidence gaps and prioritize analyses that support product value demonstration.
Partner with R&D and Product Management to inform design considerations and clinical endpoints based on real-world data insights.
Mentor and support junior analysts and team members in epidemiologic and statistical methods.
Engage with external stakeholders (KOLs, clinicians, researchers) to validate findings and ensure clinical relevance