Senior Data Analyst – Certification 3.0

Joint Commission•Oakbrook Terrace, IL

34d•$96,000 - $120,000

About The Position

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. The analyst will work with large healthcare datasets; support the development, testing, validation, and implementation of quality measures and certification criteria; and assess measure reliability, validity, risk adjustment, benchmarking, and performance variation. The role also involves building scalable analytical datasets and pipelines, working with cloud-based platforms such as Databricks, and creating reusable, documented, reproducible data assets and workflows. The position translates complex findings into business and product recommendations, develops presentations, dashboards, visualizations, and written summaries, and partners with product, clinical, business, and technology teams. It also supports evaluation of new datasets and vendors, predictive analytics and advanced modeling initiatives, and ongoing evolution of the certification model through learning and experimentation with emerging methods and technologies.

Requirements

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 performing analytics in a cloud-based computing environment, such as Databricks.
Proficiency in R or Python for data management, analysis, and reproducible workflows; R is preferred.
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.

Nice To Haves

Experience with CMS’s Virtual Data Research Center (VRDC) environment.
Experience specific to the 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.

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 technical and non-technical audiences.
Support advisory councils, leadership discussions, and product development initiatives with data-driven insights.
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.
Work collaboratively across functions, give and receive feedback constructively, and contribute to a positive, inclusive, mission-driven team culture.