Senior Data Scientist

The Opportunity at Komodo Health

Team: The Research team, within Komodo's Engineering organization, ensures that the analytical and statistical methods powering Komodo's data products are rigorous, reliable, and grounded in sound research methodology. We operate at the intersection of engineering, data science, and health services research — developing and validating methodologies, enabling HEOR/RWE research, and applying AI-assisted innovation to open technical problems across the company. Our work directly shapes the trustworthiness of the insights Komodo delivers from the Healthcare Map.

Mission: This role exists to advance Komodo's projection methodology — the statistical models that translate observed claims into national and subnational market estimates — and to ensure these models perform well in the real world and earn customer trust. As a Data Scientist on the Research team, you will take ownership of projection model quality: evaluating model performance where ground truth is scarce, engaging with customers to address their questions and concerns, and contributing to model design and implementation alongside engineering partners. Your work sits at the core of how customers trust and act on Komodo's market-level insights.

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

• Model Ownership: Became the go-to expert on Komodo's national and subnational projection models — their data foundations, assumptions, and estimation framework
• Rigorous Evaluation: Established an evaluation practice and diagnostic tooling that surface accuracy issues, drift, or bias early, drawing on creative use of benchmarks where ground truth is hard to obtain
• Customer Trust: Resolved customer-raised anomalies through systematic root-cause investigation and clear methodological communication, strengthening confidence in Komodo's market estimates
• Methodology Advancement: Contributed to model design, implementation, and validation in partnership with engineering, raising the methodological bar across releases

You will accomplish these outcomes through the following responsibilities…

• Analyze large-scale Komodo healthcare data using SQL and Python or R to assess projection model inputs, outputs, and behavior across therapeutic areas and geographies
• Design and run evaluation studies — constructing benchmarks, consistency and uncertainty quantification — and build diagnostic tooling that makes model behavior fast to assess and debug
• Triage and investigate questions from customers and customer-facing teams; reproduce reported issues, form hypotheses, and isolate root causes through systematic analysis
• Prepare and deliver clear methodological explanations — briefs, walkthroughs, and direct customer discussions — that translate model mechanics into answers customers can act on
• Review and contribute to model code, specifications, and design documents in partnership with product engineering; validate changes before and after release
• Maintain methodology documentation and evaluation reports; track model behavior across data refreshes and releases, flagging emerging issues early

What you bring to Komodo Health:

• Graduate training (MS/PhD) in Statistics, Data Science, or a related quantitative field, or equivalent applied experience
• 5+ years of industry experience applying statistical modeling and estimation to large-scale real-world healthcare data
• Deep familiarity with US healthcare claims data — the coding ecosystem (ICD, CPT/HCPCS, NDC), how drugs are billed across medical and pharmacy benefits, the distinction between open and closed data sources and its analytical implications, and how common data-generation and processing issues manifest in downstream analytics
• Experience evaluating model quality when ground truth is limited, with the creativity to design rigorous validation approaches under that constraint
• Strong diagnostic and critical-thinking skills: able to take an ambiguous question ("this number looks wrong"), form hypotheses, and systematically isolate root cause with minimal oversight
• Comfort engaging directly with customers on technical topics — listening well, explaining methodology accessibly, and maintaining credibility under scrutiny
• Working proficiency in SQL and in Python or R for large-scale data analysis and statistical modeling

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

• Direct experience with projection or extrapolation methodology — estimating population-level volumes from partial samples (e.g., sample-to-national projection, market sizing, weighting and calibration) — is a strong plus
• Experience with Bayesian statistics and its application to real-world estimation problems
• Fluency with AI-assisted development tools (coding copilots, agentic workflows) to accelerate analysis, prototyping, and documentation

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