Job Description

Department BSD OBG - Uro About the Department The Section of Urogynecology and Reconstructive Surgery is part of the Department of Obstetrics and Gynecology. The Urogynecology team provides a personalized and integrated patient care experience across 6 fully equipped clinical sites to allow women with pelvic floor disorders to have world-class urogynecologic care close to their homes. The section includes 5 board-certified urogynecologic surgeons and 5 advanced practice providers who work collaboratively to care for women with pelvic floor disorders. Teaching, research, and the highest quality clinical care are top priorities for the section. Urogynecology and Reconstructive Pelvic Surgery at UC Medicine offer patients participation in innovative clinical research trials. Job Summary The Section of Urogynecology and Reconstructive Surgery is part of the Department of Obstetrics and Gynecology. The Urogynecology team provides a personalized and integrated patient care experience across 6 fully equipped clinical sites to allow women with pelvic floor disorders to have world-class urogynecologic care close to their homes. The section includes 5 board-certified urogynecologic surgeons and 5 advanced practice providers who work collaboratively to care for women with pelvic floor disorders. Teaching, research, and the highest quality clinical care are top priorities for the section. Urogynecology and Reconstructive Pelvic Surgery at UC Medicine offer patients participation in innovative clinical research trials. This role involves performing a broad range of operational activities, including collecting, organizing, visualizing, and analyzing research data. The job also includes data manipulation, statistical applications, programming, analysis, and modeling, with an emphasis on implementing state-of-the-art methodologies for imaging and data analysis. The individual may contribute to publications and presentations based on their work. Candidates should have a degree in statistics, biostatistics, or a related field. Proficiency in statistical programming (or related languages), experience with REDCap, and familiarity with software such as R, Python, SAS, SPSS, or Stata are required. The ability to work effectively in a multidisciplinary, collaborative environment is essential. Responsibilities Assists in analyzing data to extract applicable information and supports research projects for various programs and initiatives. Supports staff or faculty with data manipulation, statistical applications, programming, analysis, and modeling as needed. Collects, organizes, and analyzes data from internal university systems and external sources. Maintains and analyzes statistical models, performs maintenance on large datasets, and collaborates with IT resources. Works with researchers to design, implement, and monitor research projects, primarily responsible for data analysis and presentation. Assists in developing research objectives, sampling, randomization, and data collection procedures. Prepares tables and statistical procedures for reports and research studies. Collaborates with research support personnel to monitor data quality. Performs other related work as needed. Minimum Qualifications Education: A college or university degree in a related field. Work Experience: Less than 2 years of relevant experience. Certifications: None specified. Preferred Qualifications Degree in statistics, biostatistics, or a related field. Experience in an Academic Medical Center. Experience supporting physicians/faculty and leadership roles. Preferred Competencies Excellent written and oral communication skills. Strong organizational and problem-solving abilities. Collaborative mindset and attention to detail. Ability to work independently. Proficiency with digital collaboration tools (Zoom, MS Teams, etc.) and MS Office Suite. Working Conditions Ability to use a computer for extended periods. Application Documents Resume (required) Cover Letter (required) Applications must be uploaded via the 'My Experience' page, in the 'Application Documents' section. #J-18808-Ljbffr The University Of Chicago

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