In partnership with the Centers for Disease Control and Prevention (CDC), ICAP is conducting Population-based HIV Impact Assessments (PHIA) in up to 20 PEPFAR-supported countries. Each PHIA will define the status of the national HIV epidemic, guide global and local allocation of funding and resources based on evidence, and integrate capacity building of country stakeholders in the design, conduct, analysis, and use of PHIAs.
Reporting to the Statistical Program Manager, the Statistician/SAS Programmer will execute Statistical Analysis Plans (SAPs) according to project specifications.
- Provide statistical programming expertise to project teams (25%)
- Write and execute statistical programs for the creation of tables, figures, listings, and analysis databases (25%)
- Work with the data management team to ensure data sets are ready for analysis or dissemination (15%)
- Write SAS code for Macros and utilize SAS Macro library (15%)
- Review Analysis plans in preparation for programming of planned and ad hoc analyses (5%)
- Ensure all programming activities and processes are conducted according to the PHIA project standard operating procedures and/or sponsor requirements (5%)
- Participation in project meetings (5%)
- Performs other related duties as directed (5%)
- Requires a Bachelor's Degree in Statistics, Biostatistics, Computer Science or related discipline, or equivalent in education and experience, with at least four (4) years of related experience.
- Minimum of one year of applicable SAS Programming experience
- Demonstrated experience with statistical programing with a high level of organization, autonomy, technical skill, and team orientation
- Strong organizational skills, including the ability to balance multiple tasks simultaneously
- Excellent organizational and oral/written communication skills required
- Master’s Degree or PhD in Statistics, Biostatistics, Computer Science or related discipline, or equivalent in education and experience
- Experience in HIV related field
- Knowledge of large scale survey analyses and geospatial analysis methods