Staff Data Analyst, Healthcare

Kairon Health•New York, NY

About The Position

Kairon Health builds software for healthcare organizations responsible for large patient populations across many physician practices. Our platform helps customers identify where care delivery is breaking down, decide what to do about it, track the operational response, and measure whether the intervention worked. Kairon is not a dashboard company. Our analytics are embedded directly into operational workflows: the same system that surfaces a problem also identifies the relevant patients, tracks the action taken, captures qualitative context from the field, and measures outcomes using methodology that matches how government programs and insurers actually calculate performance. We work with messy, high-stakes healthcare data from Medicare programs, commercial payers, electronic health records, hospital discharge feeds, labs, pharmacies, and other sources. These feeds are late, inconsistent, contradictory, and subject to unannounced format changes. Our transformation layer currently includes roughly 85 SQL routines producing approximately 200 metrics across multiple customers. The platform has already demonstrated measurable impact, driving 60x ROI at across one customer’s network in 2025, using tenure-controlled before/after analysis. We are a small team of fewer than 15 people. Everyone is close to customers, product, data, and decisions. Position Overview Kairon Health is hiring a Staff Data Analyst, Healthcare to build and own the analytical engine behind our product. This is not a support analyst role. It is not a report-building role. The work you do will become part of the product itself: metric methodology, data validation, outcome measurement, causal analysis, and the analytical logic that customers rely on to make operational and financial decisions. You will report directly to the CEO and work closely with product, engineering, customer-facing teams, and healthcare operators. You will be responsible for turning complex, unreliable healthcare data into trusted measurement systems that can stand up to scrutiny from executives, clinicians, payers, and government-program stakeholders. This is a senior individual-contributor role. You won’t manage people (at least initially) — you’ll own the analytical engine itself.

Requirements

5+ years experience as a data analyst, analytics engineer, data scientist, healthcare analyst, or similar role working with complex real-world data.
Strong SQL skills, including comfort working with layered transformations, messy source systems, and production analytical logic.
Experience with healthcare data such as claims, EHR data, payer feeds, Medicare programs, quality measures, value-based care, risk adjustment, care gaps, utilization, or population health.
Strong judgment about data quality, metric design, measurement bias, denominator/numerator logic, and edge cases.
Ability to reason rigorously about causality, attribution, before/after comparisons, cohort construction, and confounding factors.
Comfort operating in ambiguity without waiting for perfectly clean requirements.
Ability to communicate analytical decisions clearly to both technical and non-technical audiences.
Interest in building productized analytics, not one-off reports.
High ownership orientation and comfort working on a small team with direct executive visibility.

Nice To Haves

Experience with value-based care, accountable care organizations, Medicare Advantage, MSSP, HEDIS, Stars, quality programs, or payer/provider performance measurement.
Experience building data validation, reconciliation, or observability systems for healthcare data.
Familiarity with dbt or similar transformation frameworks.
Experience analyzing intervention impact in operational healthcare settings.
Ability to work across both quantitative datasets and qualitative operational context.
Prior experience in an early-stage or small-company environment.

Responsibilities

Own the methodology for healthcare performance metrics across payer, EHR, claims, clinical, operational, and government-program data sources.
Design, build, and validate SQL-based analytical logic that becomes part of Kairon’s core product.
Translate messy healthcare data into reliable measures of care gaps, intervention eligibility, performance, financial opportunity, and realized outcomes.
Build validation frameworks to detect source-system issues, feed changes, missing data, contradictory data, and metric drift.
Develop before/after, cohort, tenure-controlled, and other quasi-experimental approaches to measure whether interventions actually worked.
Partner with product and engineering to embed analytics into operational workflows rather than standalone reports.
Work with customer-facing teams to understand how physician practices, care teams, and healthcare executives interpret and act on data.
Analyze qualitative workflow and sentiment information alongside quantitative data to explain not only what is happening, but why.
Help define the analytical standards Kairon uses across customers as the company scales.
Communicate findings clearly to internal and external stakeholders, including non-technical healthcare leaders.