Senior Research Data Analyst

The Opportunity at Komodo Health

This role is critical to designing and implementing data processing and analysis programming pipelines for Life Science/HEOR/RWE research studies utilizing the Komodo Healthcare Map.

Looking back on your first 12 months at Komodo Health, you will have accomplished…

• Architected end-to-end programming pipelines for large-scale healthcare data extraction, transformation, and validation using SQL to power observational research studies leveraging Komodo Healthcare Map.
• Led the implementation of analytical plans featuring complex statistical modeling in R, aligning research objectives with appropriate methodological approaches to support HEOR/RWE studies.
• Maintained high-quality standards through rigorous documentation, best coding practices, quality control processes, and version control with Git throughout the study lifecycle.
• Produced publication-ready deliverables meeting industry standards for external clients.
• Presented interim and final results to cross-functional stakeholders, incorporating feedback to refine analyses.
• Designed and implemented standardized programming modules to enhance research reproducibility and analytical efficiency across projects.

You will accomplish these outcomes through the following responsibilities…

• Collaborate with cross-functional teams to design and execute observational research studies, by developing SQL data pipelines and R-based statistical analyses.
• Validate analysis work, troubleshoot issues, and iterate on analytic approaches to ensure alignment with research protocols and study objectives.
• Support internal tool development and contribute to publications to enhance Komodo's scientific presence.

What you bring to Komodo Health (required):

• MS in Statistics, Biostatistics, Data Science, Public Health, Epidemiology, or a related quantitative field.
• 5+ years of industry experience developing production-grade SQL pipelines (querying, cleaning, transformation) for large-scale databases.
• Proficient in R (preferred), Python, or SAS for statistical programming.
• Experience with Git version control and command-line workflows.
• Hands-on experience with administrative claims, EHR, or equivalent RWD. Familiarity with healthcare data models and U.S. medical coding systems (ICD-10, CPT, NDC).
• Experience collaborating with epidemiologists/SMEs to execute research studies, with a solid understanding of epidemiological principles.
• Proven ability to implement statistical analysis (descriptive analytics, regression, hypothesis testing, and visualization).
• Adaptability to learn new tools and methods in fast-paced environments; ability to manage concurrent projects with competing deadlines.

Additional skills and experience we’d prioritize (nice to have)…

• Advanced SQL skills (dbt, query optimization).
• Experience with advanced observational study designs.
• Extensive HEOR/RWE expertise on treatment pattern analysis, LoT, HCRU/cost analysis, synthetic control arm and patient outcome research.
• Experience with health economic modeling, including Budget Impact Models (BIM) and Cost-Effectiveness Analysis (CEA).
• Advanced statistical modeling experience in PSM, survival analysis, causal inference, and bootstrapping.
• Contributions to peer-reviewed publications. 
• Exposure to RESTful APIs, R package development, or Shiny apps.

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