Emory University Data Analyst in atlanta, Georgia

Description

JOB DESCRIPTION: Creates and maintains a data dictionary and meta data. Supports efforts to ensure that data standards are developed and maintained. Ensures that the uses of data through reports and queries are accurate. Supports business and system re-engineering and architecture development to define future data needs. Serves as an organizational consultant on matters relating to databases by providing expertise to assist users in meeting their needs. MINIMUM QUALIFICATIONS: Two years of experience in processes and standards related to data OR a bachelor's degree.

Additional Details

This Data Analyst position will support the EpiModel Research Lab @ Emory University, led by Assistant Professor Samuel Jenness in the Department of Epidemiology. The EpiModel Research Lab develops epidemiological methods and software tools (http://epimodel.org/) to investigate the infectious disease transmission dynamics, with primary applications on HIV/STIs. Our research innovates at the intersection of mathematical modeling, applied epidemiology, network science, health economics, and computational epidemiology to answer questions about what drives transmission of infectious diseases within key populations and what are the best ways to prevent their spread.

This position is supported by two research grants with shared goals of modeling HIV and related STIs among gay/bisexual men in the United States. The primary project is a NIH-funded research grant to model new forms of network-based mathematical models to understand the drivers of disease transmission and prevention opportunities in 15 high-prevalence cities across the US. The second project is a Cooperative Agreement funded by the CDC to design and execute modeling research projects to inform HIV/STI prevention in collaboration with the PRISM Health lab at Emory. For both grants, the

Data Analyst would support our EpiModel Research Lab on model conceptualization, parameter estimation, development in software, and results dissemination through journal publications and software tools.

If selected, you will have the opportunity to work closely with the PI and his team to develop skills and grow your CV in a rapidly evolving, exciting, and interdisciplinary research environment of computational epidemiology, infectious disease transmission dynamics, network science, and decision analysis.

How to apply

In addition to your formal application via the Emory Careers site, please send a cover letter and CV to Dr. Jenness (sjennes@emory.edu).

In your application cover letter, please clearly and specifically describe: 1) your experience, training, and interests in computational epidemiology or related fields, including writing software code (for statistical analyses, modeling, or software development) and languages you have used; 2) your experience, training, and interests in infectious disease transmission dynamics or epidemic modeling, including types/classes of models and diseases with which you are proficient.-The successful candidate will have completed a masters or doctoral degree in a quantitative field of health sciences, including epidemiology, biostatistics, or a closely related field. We strongly encourage applications from recent PhD graduates in epidemiology seeking a postdoctoral-level research position.

The candidate will ideally have prior research experience in infectious diseases, including HIV and other STIs, for populations in the United States or globally. Experience with mathematical modeling of infectious disease transmission dynamics (epidemic modeling) is desired. Candidates with minimal mathematical modeling experience, but possessing excitement about these issues and technical savvy (a solid quantitative skillset, experience with computer programming) are encouraged to apply.-78991BR

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Job Number 15514

Job Type Regular Full-Time

Division School Of Public Health

Department SPH: Epidemiology

This position may involve the following Health and Safety issues: Not Applicable

Job Category Information Technology

Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled