University of Chicago - Chicago, IL
posted 3 months ago
The Research Data Analyst position at the Chicago Center for HIV Elimination (CCHE) within the Biological Sciences Division at the University of Chicago Medicine is a critical role aimed at supporting the center's mission to eliminate new HIV transmission events by 2041. The analyst will engage in the analysis of bio-behavioral health and network epidemiological datasets, contributing to the understanding and prevention of HIV in highly affected populations, particularly in the South Side of Chicago. This area is notable for its significant Black population, making the work of CCHE particularly impactful in addressing health disparities. In this role, the Research Data Analyst will collaborate closely with CCHE investigators to identify and apply appropriate statistical methods to address various research hypotheses. The analyst will be responsible for creating analytic datasets by merging, cleaning, and coding data from diverse sources, including behavioral surveys, electronic health records, and public health surveillance data. Documentation of source code and data management procedures will be essential, ensuring transparency and reproducibility in research outputs. The analyst will also prepare tables and figures for manuscripts, abstracts, and other scientific publications, contributing to the writing of statistical methods sections and potentially gaining authorship on published works. Presenting results to researchers, colleagues, and funders, including formal presentations at conferences, will be a key aspect of the role. Regular meetings with research staff and data analysts will facilitate discussions on proposed analyses, code sharing, and addressing methodological challenges. Additionally, the analyst will assist with power calculations and analytic strategies for new grant proposals, and may provide critical evaluations of proposed research designs, suggesting improvements and statistical analysis plans. The position requires the ability to analyze moderately complex datasets to extract meaningful information and provide professional support to faculty and staff in applying data science principles across various projects.