Data Analyst
Central Health
Overview Central Health's Data Analyst will work alongside a team of other collaborative and engaged data analysts,epidemiologists, biostatisticians and data scientists to serve as a key resource for business intelligence, performance, clinical and operational analytics for Central Health. Under the general direction of the AnalyticsQuality Manager, our Data Analyst is responsible for organizing, analyzing, and reporting on data from large EHR, clinical, financial and enrollment data sets. This analyst will act as an Epic subject matter expert for front/back-end Epic reporting development. They will also assist in the design and validation of datamarts, performance dashboards and other systems that support the needs of an integrated network of physicians, safety net providers and hospitals to advance care that is patient centered, equitable and data driven. Responsibilities Develop and maintain complex SQL and/ or Python queries to retrieve, join, and summarize data from multiple sources, initially in SQL Server and later within Snowflake. Develop, validate, and maintain analytical reports, dashboards and visual analytics (e.g., Power BI, Tableau) to communicate findings effectively to stakeholders. Use analytical reasoning to interpret trends, relationships, and outliers; synthesize findings into actionable insights for business, operational, or clinical teams. Collaborate with operational, business and clinical units to define metrics, KPIs, and performance indicators aligned with organizational goals and document business rules and transformation logic that support consistent use of data across reports. Translate complex data into clear insights and visualizations that highlight trends, opportunities, and areas for improvement. Perform data validation, reconciliation, and spot checks to ensure accuracy and reliability of data migrated from on-prem to cloud systems. Support the development of automated data pipelines and quality checks in collaboration with data engineers. Utilize SQL and Python for data querying, modeling, staging, reporting automation. Create reports and dashboards in the Epic EHR as well as reports and dashboard in Power BI. Leverage Epic Clarity and Caboodle as a primary EHR data source for analysis, ensuring data accuracy and consistency across reporting environments. Aid in the development and validation of analytic datasets within Epic Caboodle to support enterprise reporting and population health initiatives. Participate in the development of data dictionaries, metadata documentation, and validation routines. Identify and troubleshoot data anomalies and irregularities. Contribute to continuous improvement of data quality and analytic capabilities by identifying process enhancements and automating manual workflows. Work closely with Data Engineering, Integration, and Governance teams to ensure data definitions, lineage, and access controls are properly maintained. Become a data subject matter expert (SME) and understand various sources and applications of Central Health data. Performs other duties as assigned. Qualifications MINIMUM EDUCATION: Finance, Mathematics, Economics, Statistics, Actuarial Science, Computer Science, Engineering or related quantitative discipline. Hands on experience with healthcare data analysis can substitute for for specific fields of study. Work Experience: 2 years of experience in healthcare, statistics, experimental research, data science, reporting and analytics, economics, or public health. Required and 1 year of experience in SQL (preferably T-SQL) and Python scripting with an intermediate to advanced level of expertise Required. 1 year of experience in report development within Epic EMR using Clarity, Caboodle, SlicerDicer, ReportingWorkbench, Radar Preferred. Familiarity with health care claims processing including billing codes Preferred. Experience using statistical analysis software such as SAS, R, or Python. Preferred 1 year of experience with Power BI or Tableau. Required 1 year experience in Azure/ Snowflake environment. Preferred. #J-18808-Ljbffr
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