Mission and objectives

The World Health Organization Eastern Mediterranean Regional Office (WHO EMRO) works to promote health, keep populations safe, and serve vulnerable communities across the Eastern Mediterranean Region. The mission of this assignment is to strengthen data-driven decision-making through automation and applied artificial intelligence. Objectives include: - Data Automation and Integration: Improve efficiency and reliability of health data processing through automated data pipelines. - Analytics and Visualization: Support evidence-based decision-making through advanced analytics, R-based analysis, and interactive dashboards. - Digital Innovation: Apply AI-driven solutions to enhance data interpretation, reporting, and operational workflows. - Operational Efficiency: Reduce manual data handling and improve timeliness and consistency of analytical outputs. - Capacity Strengthening: Contribute to scalable and reusable data solutions aligned with WHO standards and best practices.

Context

The Online Volunteer will support the design, automation, and enhancement of data pipelines, analytical workflows, and AI-enabled applications under the guidance of the Information Systems and Analytics team. The role will involve close collaboration with public health professionals, epidemiologists, data analysts, and IT specialists to translate analytical needs into automated and AI-supported solutions. The assignment focuses on integrating data from multiple sources, developing reproducible analytics, and deploying dashboards and AI applications to support operational and strategic functions.

Task Description

The candidate will work under the supervision of the Health Emergency Information Systems Manager. The role requires strong technical skills in data automation, R programming, dashboard development, and applied AI. Experience with Python-based AI tools and collaboration platforms such as Slack is highly desirable. Key deliverables include: - Automated data pipelines for ingestion, transformation, and validation of structured and semi-structured datasets. - Analytical scripts and workflows developed in R to support routine and ad hoc analysis. - Interactive dashboards (e.g. Power BI) for monitoring, reporting, and decision support. = AI-enabled applications or workflows (e.g. Python-based models, Slack-integrated AI tools) to enhance data analysis, knowledge extraction, and automation of routine tasks. - Technical documentation and user guidance to support sustainability and knowledge transfer.

Competencies and values

Living conditions and remarks