Senior Carbon Project Data Coordinator

About the role

BURN is hiring a full-time Senior Carbon Project Data Coordinator in Nairobi. The role owns the stove-level and financial data behind BURN's carbon investor projects, tracking stoves from factory to end user, reconciling carbon databases with BI and sales data, producing investor reporting and forecasts, and automating much of this work.

Key responsibilities

• Track serialised stoves from manufacturing to end-user sale and maintain carbon databases and investor master files.
• Run QA/QC on carbon databases before verification, checking geographic completeness, consistency and duplicate or invalid customer records, and keep supporting records such as supplier invoices, purchase orders, bills of lading and customs forms.
• Build and maintain Python scripts that clean, validate and reconcile stove, shipment and sales data, and automate monthly reconciliations, investor data packs and report checks.
• Analyse project data for trends and risks, and build dashboards (Power BI or equivalent), including an automated investor reporting dashboard.
• Prepare monthly, quarterly and annual carbon deal forecasts, weekly distribution and shipment forecasts, and weekly cash forecasts, and track actual versus budgeted distribution.
• Work with supply chain, field operations, warehouse, commercial, sales operations and BI teams, support purchase order requests for investor stoves, document processes and checklists, and carry out other duties as required.

Required profile

• Bachelor's degree in finance, data science, statistics, engineering, economics or operations.
• 3+ years in data analysis, reporting or project coordination; carbon, MRV, energy or supply-chain experience is an advantage.
• Clear written and verbal communication with internal and external stakeholders.

Required skills

• Advanced Excel (lookups, pivot tables, Power Query, financial models)
• Microsoft Dynamics NAV
• Python for data analysis
• SQL and Power BI or similar dashboard tools
• Data reconciliation, QA, forecasting and budget vs actual analysis
• Proficiency with AI tools (desirable)