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Public Health Data Manager (SAS)
Our public health group is growing and we’re currently seeking a Public Health Data Manager, primarily using SAS, to work in Atlanta, GA on location at the CDC.
The Division of HIV/AIDS Prevention−Surveillance and Epidemiology (DHAP−SE) provides national leadership for HIV prevention research and surveillance and the development and testing of effective biomedical interventions to reduce HIV transmission and HIV disease progression in the United States and internationally. The purpose of these activities is to guide the development, implementation, and evaluation of evidence-based HIV prevention programs serving persons affected by, or at risk for, HIV infection. Branches of DHAP-SE include:
- The Epidemiology Branch designs and conducts epidemiologic, behavioral, and biomedical intervention studies in the United States and internationally to determine risk factors and modes of transmission of HIV infection and to reduce HIV infection and disease progression.
- The HIV Incidence and Case Surveillance Branch conducts a national program of surveillance and research to monitor and characterize the HIV/AIDS epidemic, and its determinants and impact, to guide public health action at federal, state, and local levels. This program includes surveillance of HIV infection and AIDS in collaboration with state and local health departments to provide population-based data for research, evaluation, and prevention at the national, state, and local levels.
- The Behavioral and Clinical Surveillance Branch implements scientifically rigorous HIV research studies and surveillance systems that meet critical local, state, and national HIV prevention needs for characterizing persons who are at risk for HIV infection or who have recently acquired HIV or have HIV-related morbidities. The branch also develops and demonstrates best practices of laboratory and prevention technologies to efficiently move them from development into public health practice.
The Public Health Data Manager, primarily using SAS, will manage and analyze quantitative epidemiological, clinical and/or behavioral data and provide output in the format requested. Some specific responsibilities include:
- Design and implement study database.
- Check data files for completeness; run data quality assurance programs, and coordinate with site data managers to reconcile problems.
- Write SAS code for cleaning datasets generated by studies.
- Merge data files using SAS.
- Coordinate and assist study sites in improving the uniformity of data collection.
- Combine data from sites into a central data set.
- Evaluate data errors and work to resolve data problems.
- Provide data summary reports for each study on a weekly/quarterly basis as requested.
- Work with the biostatistician to create an analysis dataset.
- Maintain detailed step-by-step description of each analysis.
- Travel to study site to resolve data cleaning/data quality issues and provide training regarding good data management practice.
- Bachelor’s degree in public health, statistics, or related field.
- 2 years SAS programming experience.
- 2 years of experience in generating SAS-based reports using a variety of methods (e.g., PROC REPORT, PROC TABULATE) and exporting those reports to other formats such as Microsoft Excel, PDF, and HTML.
- 2 years developing data management & analysis plans and data dictionaries in a public health setting.
- Skill in manipulating and cleaning data using a variety of SAS functions, formats/informats, macros, and procedures.
- Experience assisting with research papers or presentations.
- Demonstrated ability to work with multiple data sources.
- Demonstrated ability to monitor and assess data to ensure data quality, including accuracy and completeness.
- Master’s degree in public health, statistics, or related field.
- Knowledge of public health promotion programs (knowledge/experience with HIV prevention research/programs desirable)
- Knowledge of behavioral and social science research methods
- Demonstrated experience with analysis of administrative databases.
- Detail oriented and able to create meticulous documentation of variables, datasets and data attributes
- Ability to produce data dictionaries and codebooks
- Willingness to share code and work within a team to achieve desired outcomes
- Strong organizational and interpersonal skills with the ability work as a member of a diverse team.
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