Joint Commission seeks a Healthcare Research Scientist with deep expertise in causal inference and healthcare data analytics to advance our enterprise-wide research and improvement agenda. The ideal candidate will have demonstrated success in applying rigorous statistical methods to observational data, including electronic health records (EHRs) and administrative claims, to generate actionable insights that support health system improvement, accreditation strategy, and public accountability. This individual must be adept at ensuring that externally communicated findings align with the Joint Commission’s strategic goals and mission. The role involves collaboration across Joint Commissions certification, standards, and performance measurement programs and helps extend the organization's analytic capabilities in ways that promote equity and quality in healthcare delivery.

• Design and lead applied research studies that estimate associations and causal effects from non-randomized healthcare data, contribute to Joint Commissions priorities in quality measurement, accreditation and certification evaluation, and system-level learning.
• Develop and implement advanced analytic methods, including but not limited to instrumental variables, difference-in-differences, marginal structural models, propensity score-based techniques, synthetic controls, and machine learning.
• Work with JC’s diverse data resources, including accreditation findings, electronic health record (EHR) data, ORYX/eCQM submissions, and patient-level data (PLD) from participating health systems, as well as external sources such as Medicare and Medicaid claims.
• Translate research findings into accessible, policy-relevant insights for diverse audiences including regulators, hospital leaders, clinicians, and the public.
• Ensure that public-facing research outputs and communication reflect the strategic and reputational interests of the Joint Commission.
• Publish findings in peer-reviewed journals and contribute to internal strategic products, performance improvement resources, and external stakeholder briefings.
• Develop non-technical memos, briefs, and other materials to inform internal leadership decisions and support external stakeholder engagement.
• Collaborate with cross-functional teams within the Joint Commission, the National Quality Forum (NQF), and external partners to inform accreditation standards, accreditation and certification criteria, and benchmarking methodologies.
• Provide direction to and oversight of data analysts and research assistants assigned to support project work, ensuring high-quality and timely execution of analytic tasks.
• Contribute to a culture of rigor, transparency, and equity in research planning, execution, and dissemination.

Required Qualifications:

• PhD or equivalent in economics, health services research, epidemiology, biostatistics, or a related quantitative field.
• 2 years post-doctoral experience applying causal inference methods to real-world healthcare data, especially EHRs and administrative claims.
• Peer-reviewed publication record in areas such as healthcare economics, outcomes, delivery, policy, quality, or safety.
• Demonstrated success communicating analytic findings.
• Ability to independently code, execute, and troubleshoot statistical analyses in R, Stata, or Python.
• Commitment to Joint Commission’s mission to continuously improve healthcare for the public, in collaboration with key stakeholders.
• Demonstrated track record of designing and overseeing analytic projects from concept through execution, including managing scope, timelines, and outputs in research or applied settings.

Preferred Qualifications:

• Experience with Joint Commission’s quality and process measures in prior work.
• Experience conducting research within an organization where outputs must align with institutional mission and communications strategy (e.g., ASPE, CMS, AHRQ, VA, state agencies, consulting companies, etc.).
• Familiarity with predictive modeling or statistical learning methods is welcome, especially when integrated with causal inference approaches.
• Familiarity with regulatory, payer, or policy contexts (e.g., CMS Conditions of Participation, state Medicaid programs, or alternative payment models).
• Experience working in cross-functional teams, including collaborating across roles and managing project-based responsibilities without direct supervisory authority.

We offer a comprehensive benefit package. For a complete overview of our benefits package, please visit our Joint Commission Career Page