Program Management Specialist
Role Overview
We are seeking an experienced Program and Project Management Specialist to join our team. The successful candidate will play a pivotal role in ensuring effective project planning, management, and evaluation across all areas of the organization. This role requires a combination of strategic thinking, meticulous planning, and strong collaboration skills to drive successful project outcomes.
Responsibilities
Project Management:
Monitoring & Evaluation:
Data Analysis:
- Work collaboratively with teams to define project parameters before initiation, including roles & responsibilities, reporting tools, timeline, KPIs, actions, and deliverables.
- Oversee planning and scheduling to ensure the STEM Mentorship, livelihood program and other ad hoc programs are delivered on time and with an organized structure.
- Implement project management tools and track their usage.
- Schedule and lead regular project meetings to evaluate progress, address risks, issues, dependencies (RAID), and escalate as necessary.
- Develop one-pagers describing all projects, key activities, approaches, outcomes, and impacts in collaboration with teams.
- Produce and conduct case studies, best practices, lessons learned, and project audit documents for internal and external use.
Monitoring & Evaluation:
- Develop KPIs & Metrics for grant/donor and organizational success in collaboration with all teams.
- Develop Monitoring and Evaluation plans for all projects.
- Ensure that all metrics required to be reported back by teams are included in the Monitoring and Evaluation plans for the grant area, and that necessary data is collected.
- Conduct data quality assessments to ensure accurate and consistent reporting.
- Verify data and information periodically on a sample basis.
- Conduct quality checks on teams' outputs before publication.
- Develop quality program reports incorporating past learning.
- Develop and ensure the utilization of program monitoring tools, including one-page strategic plans, pre and post-training tests, surveys, discussion guides, etc.
Data Analysis:
- Conduct data quality assessments to ensure reported data is validated, accurate, and consistent.
- Ensure the quality of data reported and verify data and information periodically on a sample basis.
- Develop and conduct quality checks on teams' outputs before publication.
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