Healthcare Data Scientist: Causal Inference & Impact

Joint Commission International; Northern (KY); Hybrid; USD 106,000 - 138,000; Full time

Job summary

Joint Commission International seeks a Healthcare Research Scientist with deep expertise in causal inference and healthcare data analytics to advance enterprise-wide research and improvement.

The role collaborates across accreditation, certification and performance measurement programs, translating findings into policy-relevant insights for health systems, regulators, and the public. A PhD and post-doctoral experience in causal methods are required.

Qualifications

• PhD or equivalent in economics, health services research, epidemiology, biostatistics, public policy, or a related quantitative field.
• 2 years post-doctoral experience applying causal inference methods to real-world healthcare data, especially administrative claims.
• Peer‑reviewed publication record in areas such as healthcare economics, outcomes, delivery, policy, quality, or safety.
• Ability to independently code, execute, and troubleshoot statistical analyses in R, Stata, or Python.

Responsibilities

• Design and lead applied research studies that estimate associations and causal effects from non-randomized healthcare data.
• Develop and implement advanced analytic methods, including instrumental variables, diff-in-differences, regression discontinuities, marginal structural models, propensity scores, synthetic controls, and machine learning.
• Collaborate with cross-functional teams to translate research findings into policy-relevant insights for diverse audiences.
• Publish findings in peer-reviewed journals and contribute to internal strategic products and external stakeholder briefings.

Skills

Causal inference

Statistical analysis

R/Stata/Python

Education

PhD in economics/health services research/epidemiology/biostatistics/public policy

Tools

R

Stata

Python

Job description

Joint Commission International seeks a Healthcare Research Scientist with deep expertise in causal inference and healthcare data analytics to advance enterprise-wide research and improvement.

The role collaborates across accreditation, certification and performance measurement programs, translating findings into policy-relevant insights for health systems, regulators, and the public. A PhD and post-doctoral experience in causal methods are required.