Background

Systems for Development (S4D) Consulting is a US-based IT consulting and digital transformation firm focused on transforming organizational performance through sustainable information and communication technology solutions. Incorporated in the United States, with operational branches in Ghana, Rwanda, Zambia, and Uganda, S4D specializes in delivering innovative digital solutions that help organizations across government and private sectors optimize operations, improve efficiency, strengthen decision-making, and achieve measurable impact. As part of its growing digital health and AI portfolio, S4D is seeking a Web App Developer to support the development of the National Digital Health Intelligence Center (NDHIC) in Zambia.

The Ministry of Health Zambia, in collaboration with implementing partners, is advancing the establishment and operationalization of the National Digital Health Intelligence Center (NDHIC). The Center is envisioned as a national digital decision intelligence platform that will strengthen data driven decision making through enhanced integration, analysis, visualization, and use of health data across the health sector.

As part of this effort, the first use case being supported by S4D is the Predictive Stock Intelligence Engine (PSIE). The PSIE leverages machine learning to predict stock out risks for health commodities, providing supply chain planners with early warning alerts and actionable insights to help prevent service disruptions at facility, district, provincial, and national levels.

The initiative has completed requirements gathering, system architecture design, and design session validation. We are now looking for a Web App Developer to lead the build-out of the application layer, translating approved UI designs into a production-grade web application, integrating ML model endpoints, and deploying the solution on the hosting infrastructure.

Role Summary

The developer will own the end-to-end delivery of the PSIE application layer, from approved mockups through to deployed, production-ready dashboards and interfaces. The role bridges front-end development, API integration, and infrastructure deployment, working closely with the data engineering and ML engineering teams (who deliver trained stock-out prediction models).

Key Responsibilities

Application Development

• Build the Predictive Stock Intelligence Engine platform from approved wireframes and design specifications, including stock-out risk dashboards, commodity monitoring views, alert panels, and reporting interfaces
• Implement interactive data visualizations — stock-out probability indicators, months-of-stock (MOS) trend lines, consumption patterns, risk heat maps, and geographic drill-downs (national → provincial → district → facility)
• Develop user workflows including filtering, drilldowns, threshold-based alerting, commodity segmentation views, and export functionality (PDF, Excel)
• Build role-based views and navigation for different user profiles (supply chain planners, provincial pharmacists, national M&E officers, warehouse managers)

API and ML Model Integration

• Integrate the front-end with ML model inference endpoints (REST APIs) to surface stock-out risk predictions, near stock-out flags, and recommended redistribution actions
• Connect to the data platform’s serving layer (Gold layer of the medallion architecture) for live and historical stock, consumption, and distribution data
• Implement real-time and scheduled data refresh logic across dashboard components
• Handle API error states, loading states, and data latency gracefully in the UI

Infrastructure and Deployment

• Set up and manage the hosting environment for the application — whether cloud, on-premises, or hybrid — based on the infrastructure decisions made during implementation
• Configure CI/CD pipelines for automated testing, build, and deployment
• Implement authentication, authorization, and role-based access control (RBAC)
• Ensure the application meets security, performance, and availability requirements appropriate for a government health platform
• Monitor application performance and set up logging and alerting

Collaboration and Handover

• Work with the data engineering team to define and consume API contracts from the data platform
• Coordinate with the ML engineering team on model endpoint specifications, input/output schemas, and versioning
• Participate in UAT cycles with MoH stakeholders, incorporating feedback into iterative releases
• Produce technical documentation covering application architecture, deployment procedures, and maintenance guides
• Support knowledge transfer and capacity building for MoH/ICT teams to ensure long-term sustainability

Required Qualifications

• 4+ years of professional experience in web application development
• Strong proficiency in a modern front-end framework (React, Vue, or Angular) with experience building data-heavy dashboards and visualization interfaces
• Experience with data visualization libraries for rendering charts, maps, and interactive analytics views
• Proven experience integrating front-end applications with REST APIs and handling asynchronous data flows
• Hands-on experience deploying and managing applications across cloud, on-premises, or hybrid environments
• Experience with containerization and container orchestration
• Familiarity with CI/CD practices and tooling
• Experience implementing authentication and RBAC in web applications
• Strong understanding of responsive design, accessibility, and cross-browser compatibility

Preferred Qualifications

• Experience working in health systems, public health informatics, or supply chain analytics
• Experience consuming ML model endpoints and surfacing predictions or risk scores in user-facing applications
• Exposure to data platform architectures (medallion/lakehouse patterns, data warehouses)
• Prior work with government or multilateral stakeholders in Sub-Saharan Africa
• Experience supporting UAT processes and iterating based on non-technical stakeholder feedback

Key Competencies

• Ability to translate design mockups into pixel-accurate, performant interfaces without extensive design hand-holding
• Comfort working across the stack from UI components to API integration to infrastructure deployment
• Strong communication skills, particularly the ability to explain technical decisions and trade-offs to non-technical stakeholders
• Self-directed and able to work in a small, distributed team with minimal oversight
• Pragmatic approach to technology choices focused on what works reliably in the operating context rather than what’s newest
• Platform-agnostic mindset able to assess and work with whatever hosting model fits the operational reality

Deliverables

• Deployed PSIE with all approved dashboard, monitoring, alert, and reporting views
• Integrated ML model endpoints surfacing stock-out risk predictions and near stock-out flags
• Hosting infrastructure setup with CI/CD, monitoring, and RBAC
• Technical documentation and deployment runbooks
• Handover and capacity-building sessions with the MoH/ICT team

• Build the Predictive Stock Intelligence Engine platform from approved wireframes and design specifications, including stock-out risk dashboards, commodity monitoring views, alert panels, and reporting interfaces
• Implement interactive data visualizations — stock-out probability indicators, months-of-stock (MOS) trend lines, consumption patterns, risk heat maps, and geographic drill-downs (national → provincial → district → facility)
• Develop user workflows including filtering, drilldowns, threshold-based alerting, commodity segmentation views, and export functionality (PDF, Excel)
• Build role-based views and navigation for different user profiles (supply chain planners, provincial pharmacists, national M&E officers, warehouse managers)
• Integrate the front-end with ML model inference endpoints (REST APIs) to surface stock-out risk predictions, near stock-out flags, and recommended redistribution actions
• Connect to the data platform’s serving layer (Gold layer of the medallion architecture) for live and historical stock, consumption, and distribution data
• Implement real-time and scheduled data refresh logic across dashboard components
• Handle API error states, loading states, and data latency gracefully in the UI
• Set up and manage the hosting environment for the application — whether cloud, on-premises, or hybrid — based on the infrastructure decisions made during implementation
• Configure CI/CD pipelines for automated testing, build, and deployment
• Implement authentication, authorization, and role-based access control (RBAC)
• Ensure the application meets security, performance, and availability requirements appropriate for a government health platform
• Monitor application performance and set up logging and alerting
• Work with the data engineering team to define and consume API contracts from the data platform
• Coordinate with the ML engineering team on model endpoint specifications, input/output schemas, and versioning
• Participate in UAT cycles with MoH stakeholders, incorporating feedback into iterative releases
• Produce technical documentation covering application architecture, deployment procedures, and maintenance guides
• Support knowledge transfer and capacity building for MoH/ICT teams to ensure long-term sustainability

• Web application development
• Front-end framework (React, Vue, or Angular)
• Data-heavy dashboards and visualization interfaces
• Data visualization libraries
• REST APIs integration
• Asynchronous data flows
• Deploying and managing applications (cloud, on-premises, hybrid)
• Containerization and container orchestration
• CI/CD practices and tooling
• Authentication and RBAC implementation
• Responsive design
• Accessibility
• Cross-browser compatibility
• ML model endpoints consumption
• Data platform architectures (medallion/lakehouse patterns, data warehouses)
• UAT process support
• Technical documentation
• Capacity building

• 4+ years of professional experience in web application development
• Strong proficiency in a modern front-end framework (React, Vue, or Angular) with experience building data-heavy dashboards and visualization interfaces
• Experience with data visualization libraries for rendering charts, maps, and interactive analytics views
• Proven experience integrating front-end applications with REST APIs and handling asynchronous data flows
• Hands-on experience deploying and managing applications across cloud, on-premises, or hybrid environments
• Experience with containerization and container orchestration
• Familiarity with CI/CD practices and tooling
• Experience implementing authentication and RBAC in web applications
• Strong understanding of responsive design, accessibility, and cross-browser compatibility
• Experience working in health systems, public health informatics, or supply chain analytics (Preferred)
• Experience consuming ML model endpoints and surfacing predictions or risk scores in user-facing applications (Preferred)
• Exposure to data platform architectures (medallion/lakehouse patterns, data warehouses) (Preferred)
• Prior work with government or multilateral stakeholders in Sub-Saharan Africa (Preferred)
• Experience supporting UAT processes and iterating based on non-technical stakeholder feedback (Preferred)