Job Specifications
Job Title: Data Scientist Associate, NCDR Analytics
Department: Research & Analytics – NCDR
Reports To: Team Lead, Data Science, NCDR Analytics
Position Overview
The Data Scientist Associate will support the National Cardiovascular Data Registry (NCDR) by applying modern data science methods to advance clinical insights and strengthen analytic capabilities. This role is ideal for someone who is passionate about healthcare data, machine learning, and improving outcomes in cardiovascular care. The position will work closely with cross-functional teams to design, develop, and deliver data-driven solutions that support NCDR’s mission and strategic objectives.
Key Responsibilities
Develop data science solutions—including machine learning models, statistical analyses, and NLP workflows—to generate insights for both internal teams and external NCDR stakeholders.
Conduct exploratory data analysis (EDA) on large clinical registry datasets to uncover patterns, inform decision-making, and enhance registry products and services.
Collaborate with internal groups, IT teams, and other stakeholders to support data science initiatives and ensure alignment across program areas.
Create dashboards, visualizations, and reporting tools using platforms such as Power BI to communicate complex findings in a clear, actionable manner.
Integrate external data sources, such as claims data, registry datasets, clinical information, and patient-reported outcomes (PRO), to enrich analytic outputs and identify trends.
Follow established documentation standards, coding conventions, and best practices to ensure reproducibility, clarity, and effective teamwork across the data science group.
Apply relevant analytic techniques that support real-world evidence (RWE) initiatives and other NCDR research priorities.
Comply with privacy, security, and regulatory requirements by completing mandatory training and following data protection policies.
Required Qualifications
Bachelor’s degree in a related field (e.g., Data Science, Statistics, Public Health, Computer Science, or similar).
Hands-on experience using Python or R, as well as proficiency in SQL for querying and manipulating data.
Familiarity with machine learning concepts, statistical modeling, working with unstructured data, and operationalizing data science workflows.
Experience with data visualization tools such as Power BI, Tableau, ggplot, or plotly.
Strong communication skills with the ability to explain technical analyses to non-technical audiences.
Proficiency with Microsoft Office tools; exposure to Microsoft Access, Visio, or SharePoint is helpful.
About the Company
We take immense pride in consistently being recognized as one of the fastest-growing staffing firms in the U.S. by Staffing Industry Analysts (SIA). As a consistent Inc. 5000 award winner and a Top Workplace in the markets we serve, we remain dedicated to delivering high-impact talent solutions while fostering meaningful connections with our clients, candidates, and communities. Our team delivers tailored talent solutions designed to meet the unique needs of our partners in the areas of IT/Engineering, Accounting/Finance, Pr...
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