Manager leading healthcare quality initiatives through data expertise, analytics, and KPI tracking. Collaborating with cross-functional teams for performance enhancement and quality reporting.
Responsibilities
Applied deep expertise in healthcare terminology, clinical data standards, and quality metrics (NQMs, HEDIS) to enhance quality reporting accuracy.
Partnered with leadership to define and track KPIs, driving measurable improvements in patient safety, effectiveness, compassion, and care quality.
Developed Python workflows (pandas, NumPy, matplotlib) to aggregate, clean, and validate multi-source healthcare data, reducing data errors and improving consistency.
Led data quality assessments to identify anomalies and inconsistencies, strengthening the reliability of clinical datasets used in quality measure reporting.
Created and enforced data validation rules, ensuring compliance with organizational data governance protocols and regulatory standards.
Produced clear, actionable reports and executive summaries that informed strategic decisions and supported quality improvement initiatives.
Partnered with data science teams to automate data transformation pipelines, accelerating data preparation and enabling faster model deployment.
Conducted audits across multiple clinical data sources, reconciling structured SQL datasets with patient-level XML records for accurate quality measure reporting.
Designed Tableau and Power BI dashboards that provided real-time performance insights and reduced manual reporting workload.
Successfully managed remote projects with cross-functional teams across the U.S., delivering all milestones on schedule.
Requirements
Requires Bachelor’s degree, in Engineering (any), Information Technology, or a directly related field plus seven (7) years of experience in Data engineering and data analytics.
Requires six (6) years of experience in Microsoft SQL;
Three (3) years of experience in the following: Python;
One (1) year of experience in the following: Tableau, Power BI.
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