Associate, NCDR Data Scientist

Position Title

Associate, NCDR Data Scientist

Washington, DC, United States

Clinical Measurement

The data scientist plays a key role in advancing the analytical engine behind the National Cardiovascular Data Registries (NCDR). This role drives the development of clinical datasets, powers quality and performance measure reporting, and strengthens ACC’s registry science through advanced analytics, SQL‑based measure implementation, and emerging AI‑driven solutions. You’ll help shape smarter, more efficient processes by validating and optimizing registry data and models, ensuring accuracy and high‑quality outputs that directly support clinicians and participants nationwide.

Success in this role calls for strong analytical thinking, problem‑solving skills, and the ability to stay organized in a dynamic, matrixed environment while collaborating closely with the NCDR Data Science and Analytics team.

• Perform frequency and other possible analysis, e.g., descriptive statistical, on data element submission rates and clinical metric reporting application to inform dataset development by internal staff and volunteer work groups.
• Conduct assessments (e.g. rule-based, correlation analysis) to identify redundant data elements and recommend reductions as well as standardization across datasets.
• Manage registry data elements for automated upgrades.
• Develop ongoing monitoring views into data submission rates to inform threshold submission requirements, shifts in clinical characteristics at the facility and patient level, and other dataset‑based analysis, such as for clinical research purposes, as well as potential correlations within data element submission completeness to complexity of patient populations to support customer coding.
• Perform analysis to support clinical measurement staff and volunteer work groups and Steering committees develop and report meaningful measures as well as identify candidate measures to be sunset due to low reporting frequencies associated with low data element capture completeness provided in submissions.
• Collaborate with clinical measure development and IT teams to propose data visualization approaches to increase ease of interpretability of measures for customers.
• Develop ongoing monitoring of clinical measures reported across registry dashboards to identify to extent reasonable variations in outcomes.

• Perform analysis to support clinical measurement staff and volunteer work groups and Steering committees develop and report meaningful measures as well as identify candidate measures to be sunset due to low reporting frequencies associated with low data element capture completeness provided in submissions.
• Collaborate with clinical measure development and IT teams to propose data visualization approaches to increase ease of interpretability of measures for customers.
• Develop ongoing monitoring of clinical measures reported across registry dashboards to identify to extent reasonable variations in outcomes.

• Collaborate with staff and volunteer committee and work group members in identify opportunities to align with external structured terminologies and/or apply large language modeling (LLM) approaches to ease effort associated with data capture by customers for submission to NCDR.
• Assist on projects as identified, such as to explore novel mechanisms to import clinical data to expand view of patient care and outcomes including applications to clinical measurement reporting; or to support efficiencies in data export out of electronic medical record systems or other data environments, e.g., lakes, for customers or third‑parties, e.g., certified software vendors.

• Learn the NCDR Common Data Model (CDM) structure to be able to interpret code and conduct quality‑checks for measures and models.
• Monitor and analyze AI industry trends and identify opportunities to apply AI techniques to improve internal efficiency assess customer adoption of AI in registry contexts.
• Use analytic approaches through tools such as SQL and Excel to identify opportunities for process…