Real World Evidence Manager

Summary

iRhythm Technologies is a digital healthcare company focused on cardiac health solutions and data-driven patient care. The Real World Evidence Manager leads quantitative real-world evidence and health economics analyses, including study execution, statistical programming, economic modeling, and scientific dissemination to support payer coverage, health system contracting, and product strategy.

Responsibilities

• 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
• 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
• 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)
• 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
• 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

Skills

• ▪ 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
• ▪ 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

Qualifications

Must Haves

• ▪ 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

Nice to Haves

• ▪ 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