The Information Services Unit (ISU) Data Manager is responsible for the cleansing, analysis, and dissemination of high-quality data for Philadelphia’s Ending the HIV Epidemic (EHE), Ryan White (RW) care, and HIV prevention services. This full-time position is part of the Evaluation Team of the Information Services Unit of the Philadelphia Department of Public Health’s Division of HIV Health (DHH). The ISU Data Manager analyzes provider reports and client-level data exports from the RW CAREWare database, the CDC EvaluationWeb database, and other data sources using statistical software and methods. This position plays a key role in promoting data quality, identifying and resolving data inconsistencies, and developing processes that improve the accuracy, completeness, timeliness, and usability of program data. In support of EHE and prevention services, the Data Manager matches HIV testing data to Surveillance and Partner Services data and evaluates and provides feedback on outcomes related to HIV testing, PrEP, and navigation services. The ISU Data Manager analyzes and provides feedback on RW data for the 9-county Philadelphia EMA (eligible metropolitan area). In support of the EHE plan, the Data Manager provides technical assistance on the EHE Triannual reporting module, reports on EHE benchmarks, and combines, cleans, analyzes, and reports data from different data sources across the HIV continuum into one data system. The Data Manager also provides ad hoc data analysis and reporting to support programmatic planning, quality improvement, and decision-making. This includes responding to emerging data needs, developing reports and analysis to answer programmatic questions, identifying areas of concern, and translating data findings into actionable information for DHH leadership, programs, and other stakeholders. The position is responsible for promoting data quality by providing feedback, building capacity, offering technical support to DHH’s funded subrecipients, and through input in the ISU’s development, improvement, and implementation of data systems and strategies that optimize statistical efficiency and quality.
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Job Type
Full-time
Career Level
Mid Level