UNIV - Senior Research Associate - Data Manager - ECHO - Department of PHS

Medical University of South CarolinaCharleston, SC
2d

About The Position

The SC ECHO cohort in the Department of Public Health Sciences at the Medical University of South Carolina invites Master-level Data Managers to apply for a position within our team. The position will be responsible for database management, ensuring data quality and regulatory compliance, overseeing medical record abstraction, and developing efficient data workflows to support research and reporting. The Data Manager will also be responsible for contributing to daily activities of the study. This position is for biostatisticians or epidemiologists with a master's degree in biostatistics, epidemiology, applied statistics or related fields, and with professional experience in cohort studies.

Requirements

  • A master's degree in statistics, epidemiology, biostatics or related field.
  • Candidates should be able to work independently, have experience and ability in data analysis and statistical programming, and excellent oral and written communication skills.

Nice To Haves

  • At least 1 year of professional programming experience in R (preferred), SAS and/or Winbugs is required (evidence of experience based on classwork or certifications can be substituted for professional experience).

Responsibilities

  • Conduct data analysis for scientific publications. Collaborate with national ECHO Data Analysis Center.
  • Utilize data management system to maintain participant records, track recruitment progress and study milestones, and generate recruitment and study visit reports for PI and the study team of the ECHO program at MUSC. Troubleshoot workflow issues and train new staff on proper use of data management system for participant tracking.
  • Responsible for data quality checks and data reconciliation. Monitor data completeness. Train staff on data entry standards. Support audits and regulatory reviews by providing clean, verified datasets.
  • Automate data abstraction from medical records, ensure accuracy and completeness of abstracted data through verification and quality checks, and track productivity metrics.
  • Assist with data sharing and archiving per study and sponsor requirements.
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