Senior Data Scientist

At Komodo Health, our mission is to reduce the global burden of disease. And we believe that smarter use of data is essential to this mission. That’s why we built the Healthcare Map — the industry’s largest, most complete, precise view of the U.S. healthcare system — by combining de-identified, real-world patient data with innovative algorithms and decades of clinical experience. The Healthcare Map serves as our foundation for a powerful suite of software applications, helping us answer healthcare’s most complex questions for our partners. Across the healthcare ecosystem, we’re helping our clients unlock critical insights to track detailed patient behaviors and treatment patterns, identify gaps in care, address unmet patient needs, and reduce the global burden of disease. 

As we pursue these goals, it remains essential to us that we stay grounded in our values: be awesome, seek growth, deliver “wow,” and enjoy the ride. At Komodo, you will be joining a team of ambitious, supportive Dragons with diverse backgrounds but a shared passion to deliver on our mission to reduce the burden of disease — and enjoy the journey along the way.

• 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

• →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

• →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

• 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

#LIRemote

At Komodo, we're not just witnessing the AI revolution – we're leading it. This is a pivotal moment in time, where being first to market with AI transforms industries and sets the bar. We've already established industry leadership in leveraging AI to revolutionize healthcare, and we expect every team member to contribute. AI here isn't optional; it's foundational. We expect you to integrate AI into your daily work – from summarizing documents to automating workflows and uncovering insights. This isn't just about efficiency; it's about making every moment more meaningful, building on trust in AI, and driving our collective success.

Komodo Health has a hybrid work model with hubs in San Francisco, New York City, and Chicago. Roles vary — some can be performed from anywhere in the country, others are scoped to a specific region, and some are based near one of our hubs. For hub-based Dragons, we're building intentional in-office rhythms alongside the flexibility that's core to how we work. Whatever your setup, expectations will always be clear before you join.

Komodo Health provides equal employment opportunities to all applicants and employees. We prohibit discrimination and harassment of any type with regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. 

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