Real World Evidence Manager

Job description

Career-defining. Life-changing. At iRhythm, you’ll have the opportunity to grow your skills and your career while impacting the lives of people around the world. iRhythm is shaping a future where everyone, everywhere can access the best possible cardiac health solutions. Every day, we collaborate, create, and constantly reimagine what’s possible. We think big and move fast, driven by our commitment to put patients first and improve lives. We need builders like you. Curious and innovative problem solvers looking for the chance to meaningfully shape the future of cardiac health, our company, and your career About This Role: The Real World Evidence Manager is a highly technical, hands-on research role that serves as an analytical engine for iRhythm’s RWE and health economics program. Reporting to the Senior Ditector, Global Value and Access Innovation, this individual manages the execution and quality of quantitative analyses that generate the clinical, economic, and real-world evidence underpinning the Zio platform’s value proposition to US payers and health systems. This role combines independent analytical execution with strong methodological rigor, carrying analytical workstreams from protocol through peer-reviewed dissemination. The RWE Manager serves as the primary programmer and model builder, producing analytical outputs that directly influence payer coverage decisions, health system contracting, and product strategy with secondary support for international (OUS) value and access workstreams. Key Responsibilities Real-World Evidence (RWE) Design & Execution ▪ Manage the execution of retrospective and prospective RWE studies using claims data (Medicare, Medicaid, commercial), EMR/EHR data, and proprietary iRhythm clinical datasets. ▪ Operationalize study protocols, analytic plans, variable definitions, and statistical methodologies appropriate for payer and peer-reviewed audiences. ▪ Apply advanced epidemiological methods including propensity score matching, instrumental variables, difference-in-differences, interrupted time series, and survival analysis. ▪ Ensure reproducibility, auditability, and documentation of all analytical pipelines. Health Economic Modeling ▪ Build and maintain sophisticated health economic models including budget impact models (BIMs), cost-effectiveness models, and payer decision-support tools. ▪ Translate clinical evidence into economic inputs with appropriate uncertainty characterization. ▪ Develop and update payer-facing economic tools that field and account teams can deploy in customer engagements. ▪ Conduct sensitivity analyses, scenario modeling, and probabilistic analyses (PSA) consistent with HTA standards. Statistical Programming & Data Infrastructure ▪ Serve as the primary statistical programmer for RWE and health economic projects, with proficiency in R, Python, SAS, or equivalent tools. ▪ Design and maintain analytical data infrastructure including datasets, codebooks, data dictionaries, and QC processes. ▪ Work with data vendors, CROs, and internal data science teams to access, clean, and validate data assets. ▪ Implement and maintain version-controlled analytical repositories (GitHub or equivalent). Scientific Communication & Publication ▪ Prepare scientific abstracts, posters, and manuscripts for ISPOR, AMCP, ACC/AHA, HRS, and peer-reviewed journals. ▪ Translate complex analytical findings into clear, audience-appropriate formats for payer, clinical, and executive audiences. ▪ Co-author or contribute to health economic dossiers, coverage submissions, and payer value tools. Cross-Functional Leadership ▪ Partner with Medical Affairs, Clinical Research, Commercial, and Payer Relations teams to align evidence generation with strategic priorities. ▪ Represent analytical workstreams in stakeholder engagements, as designated by the Director. ▪ Mentor interns and junior analysts on research methodology, data analysis, and scientific writing. Qualifications Required ▪ Masters or doctoral degree (MS, MPH, PhD) in Health Economics, Epidemiology, Biostatistics, Public Health, or a highly quantitative related field. ▪ 3+ years of progressive experience in HEOR, RWE, or health economic analytics within the pharmaceutical, biotech, diagnostics, or digital health industry (or equivalent academic/consulting background). ▪ Expert-level proficiency in at least two of: R, Python, SAS, STATA for statistical analysis and data management. ▪ Demonstrated experience designing and executing observational studies using claims or EMR data. ▪ Strong track record of health economic model development (BIM, CEA, cost-utility models). ▪ Peer-reviewed publication record or equivalent demonstrated scientific output (abstracts, posters, dossier contributions). ▪ Strong analytical judgment and ability to execute rigorous analyses and communicate methodological choices clearly. Preferred ▪ PhD in Epidemiology, Biostatistics, Health Economics, or related field. ▪ Prior experience in cardiac electrophysiology, digital diagnostics, or ambulatory monitoring. ▪ Familiarity with US reimbursement structures (CMS, Medicare Advantage, commercial payers) and their evidentiary requirements. ▪ Experience with NCQA/HEDIS measure development or quality measurement frameworks. ▪ Proficiency with data platforms such as Optum Clinformatics, IBM MarketScan, TriNetX, or Komodo Health. ▪ Tableau or equivalent visualization platform experience. Core Competencies ▪ Methodological Rigor: Applies advanced research methods with scientific independence and defensibility. ▪ Analytical Leadership: Drives analytical workstreams end-to-end with minimal supervision. ▪ Strategic Communication: Translates complex data into compelling, actionable insights. ▪ Cross-Functional Partnership: Works effectively with commercial, clinical, and policy stakeholders. ▪ Scientific Integrity: Upholds highest standards of research quality, reproducibility, and Location: Remote - US Actual compensation may vary depending on job-