Senior Data Analyst – Certification 3.0

Joint Commission; United States; On-site; USD 96,000 - 120,000; Full time

Job summary

Joint Commission is seeking a Senior Data Analyst to support a data-driven certification model across healthcare. You will analyze large healthcare datasets, develop quality measures, and translate findings into actionable recommendations for executives and product teams.

You will design scalable data pipelines, work with Databricks, and communicate complex analytics to diverse audiences while contributing to strategic decision-making and product development initiatives.

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Health Informatics, Epidemiology, Public Health, Mathematics, Healthcare Analytics, Economics or a related field.
• 3–7+ years of experience in healthcare analytics, healthcare data management, healthcare data science, or a related analytical role.
• Experience working with healthcare claims data, including Medicare, Medicaid, commercial, administrative, or value-based care datasets.
• Strong SQL skills and experience optimizing queries for large datasets.
• Experience in performing analytics in a cloud-based computing environment, such as Databricks.
• Proficiency in R (preferred) or Python for data management, analysis, and reproducible workflows.
• Experience building analytical datasets, performing data quality validation, and documenting assumptions and limitations.
• Strong analytical, problem-solving, and critical thinking skills.
• Demonstrated ability to communicate complex findings effectively to diverse audiences.
• Experience working collaboratively within cross-functional teams.

Responsibilities

• Analyze large healthcare datasets, including claims, administrative, clinical, and other real-world data sources.
• Support development, testing, validation, and implementation of quality measures, certification criteria, and performance indicators.
• Evaluate measure reliability, validity, risk adjustment approaches, benchmarking methods, and performance variation.
• Conduct exploratory analyses to identify opportunities for new healthcare quality, safety, and certification products.
• Support environmental scans and market assessments of healthcare measures, datasets, and benchmarking programs.
• Design, develop, and maintain scalable analytical datasets and data pipelines.
• Work with cloud-based data platforms, including Databricks and related modern data architecture tools.
• Perform data ingestion, transformation, validation, and quality assurance across multiple healthcare data sources.
• Contribute to reusable data assets, documented data models, and reproducible analytical workflows.
• Support implementation of healthcare interoperability standards and emerging data exchange frameworks.
• Translate complex analytical findings into clear business and product recommendations.
• Develop executive-ready presentations, dashboards, visualizations, and written summaries.
• Partner with product, clinical, business, and technology teams to define analytical requirements and support strategic decision-making.
• Communicate statistical and technical concepts to both technical and non-technical audiences.
• Support advisory councils, leadership discussions, and product development initiatives with data-driven insights.

Skills

Analytical thinking

Communication

Cross-functional collaboration

Education

Bachelor’s degree in Data Science or related field

Tools

Databricks

Power BI

Tableau

Shiny

Git

CI/CD

Job description

Overview

The Senior Data Analyst will support a next-generation, data-driven certification model that uses healthcare data, analytics, and evidence-based insights to improve quality, safety, and outcomes across the continuum of care. The role combines claims -based healthcare analytics, modern data platform fluency, data engineering readiness, and the ability to translate complex findings into actionable product, clinical, and executive decisions.

Responsibilities

Healthcare Analytics & Measure Development

• Analyze large healthcare datasets, including claims, administrative, clinical, and other real-world data sources.
• Support development, testing, validation, and implementation of quality measures, certification criteria, and performance indicators.
• Evaluate measure reliability, validity, risk adjustment approaches, benchmarking methods, and performance variation.
• Conduct exploratory analyses to identify opportunities for new healthcare quality, safety, and certification products.
• Support environmental scans and market assessments of healthcare measures, datasets, and benchmarking programs.

Data Engineering & Platform Enablement

• Design, develop, and maintain scalable analytical datasets and data pipelines.
• Work with cloud-based data platforms, including Databricks and related modern data architecture tools.
• Perform data ingestion, transformation, validation, and quality assurance across multiple healthcare data sources.
• Contribute to reusable data assets, documented data models, and reproducible analytical workflows.
• Support implementation of healthcare interoperability standards and emerging data exchange frameworks.

Insights, Communication & Product Support

• Translate complex analytical findings into clear business and product recommendations.
• Develop executive-ready presentations, dashboards, visualizations, and written summaries.
• Partner with product, clinical, business, and technology teams to define analytical requirements and support strategic decision-making.
• Communicate statistical and technical concepts to both technical and non-technical audiences.
• Support advisory councils, leadership discussions, and product development initiatives with data-driven insights.

Innovation & Future-Focused Analytics

• Evaluate new healthcare datasets, vendors, and data acquisition opportunities.
• Support predictive analytics, risk stratification, advanced modeling, and signal detection initiatives.
• Contribute to Cert 3.0 evolution through continuous learning and experimentation with emerging analytical methods and technologies.
• Stay informed about healthcare quality measurement, interoperability standards, AI applications, and industry best practices.

Success Factors

• Analytically rigorous: Approaches problems with curiosity, structure, attention to detail, and a commitment to accurate , reproducible work.
• Technically adaptable: Comfortable learning new technologies , data sources, and analytical methods; willing to develop deeper skills in data engineering, cloud technologies, and healthcare data platforms.
• Healthcare-oriented: Understands the connection between data, quality improvement, patient outcomes, healthcare operations, and certification strategy.
• Effective communicator: Creates clear data stories and translates technical findings into actionable recommendations for executives, clinicians, product leaders, and technical teams.
• Collaborative team member: Works effectively across functions, gives and receives feedback constructively, and contributes to a positive, inclusive, mission-driven team culture.

Qualifications

Required

• Bachelor’s degree in Data Science , Statistics, Computer Science, Health Informatics, Epidemiology, Public Health, Mathematics, Healthcare Analytics, Economics or a related field .
• 3–7+ years of experience in healthcare analytics, healthcare data management, healthcare data science, or a related analytical role.
• Experience working with healthcare claims data, including Medicare, Medicaid, commercial, administrative, or value-based care datasets.
• Strong SQL skills and experience optimizing queries for large datasets.
• Experience in performing analytics in a cloud-based computing environment, such as Databricks.
• Proficiency in R (preferred) or Python for data management, analysis, and reproducible workflows.
• Experience building analytical datasets, performing data quality validation, and documenting assumptions and limitations.
• Strong analytical, problem-solving, and critical thinking skills.
• Demonstrated ability to communicate complex findings effectively to diverse audiences.
• Experience working collaboratively within cross-functional teams.

Preferred

• Experience with CMS’s Virtual Data Research Center (VRDC) environment.
• Experience specific to Databricks analytic platform .
• Experience with healthcare data standards and interoperability frameworks such as FHIR, HL7, or CQL.
• Familiarity with EHR data sources and clinical data models, including Epic, Oracle Health/Cerner, Cosmos, or comparable environments.
• Experience developing, testing, or evaluating healthcare quality measures.
• Knowledge of risk adjustment, benchmarking, population health analytics, outcomes measurement, or value-based care programs.
• Familiarity with healthcare terminology and coding systems, including ICD-10, CPT, HCPCS, DRG, SNOMED, LOINC, or RxNorm .
• Experience using Power BI, Tableau, Shiny, or similar visualization tools.
• Experience with Git, CI/CD, code review, and modern software development practices.
• SAS knowledge is a plus

This job description is intended to describe the general nature and level of work performed by an employee assigned to this position. The description is not an exhaustive list of all duties, responsibilities, knowledge, skills, and abilities, and working conditions associated with this position. All requirements are subject to possible modification and reasonably accommodate individuals with disabilities.

Equal Opportunity Field

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

We are an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Min

USD $96,000.00/year

Max

USD $120,000.00/year