Requirements
Undergraduate degree in medical, scientific, biological, statistical, computer science, or related field
At least 2 years of experience in managing databases within a research environment
At least 2 year's demonstrable experience building and managing complex data collection tools using Redcap (please detail in cover letter)
At least 1 year of supervisory and staff management
Proficient in MS Excel and Access and be able to design a database, run and resolve data queries
Good Clinical Practice (GCP) certificate
Valid code 8 driver's license
Advantageous:
Experience with statistical packages e.g. STATA, SPSS, SAS or R
Knowledge of HIV & ART
Responsibilities
Research Data Management:
Institutionalize high-quality data collection, management, and quality assurance systems and processes for current studies and ARV databases using REDCap and other platforms.
Develop and implement real-time data quality assurance processes and procedures
Perform data cleaning and log data queries for investigation
Support the design of compatible and integrated systems for data coordination and sharing with research partners
Work with study Project lead and Project Manager to develop data management and quality assurance plans, including project progress monitoring tools
Develop and automate statistical dashboards on project implementation and key study variables
Prepare and extract analytic datasets, and perform analyses for PI, project lead and managers
System Design and Maintenance:
Provide oversight for collection of data from the studies, including:
Incorporating data from database or data system,
Supervise the organization, cleaning, and verifying complete data entry by research assistants and fieldworkers;
Prepare data for use in analyses by overseas and South African-based investigators.
Oversee all QC and QA processes
Ensure that data is collected and QCed as per the Quality management plan
Staff Management:
Manage staff and oversee their work.
Manage the quality of databases and supervise data-entry staff
Ensure training of and optimal implementation of all components of project data management
Train and support field-based data collection staff members
Attend project management meetings