The role

We are looking for a GIS Data Analyst to turn satellite imagery, spatial datasets and field surveys into evidence that guides decisions on climate, natural resources and livelihoods across Africa. You will join our data and analytics team and work alongside consultants in our Climate Financial Services Strategy practice. Our team helps governments, funds and financial institutions in Africa and other emerging markets with three things: planning for climate change, finding the money to act, and checking that the action works.

Areas we work in:

• Climate policy, NDCs and Just Transition: reviews of national and sector plans, institutions and financing systems.
• Climate risk and loss and damage: hazard, exposure and vulnerability analysis, and the economic cost of climate impacts.
• Climate finance and investment: GCF and GEF proposals, investment plans, pipelines of bankable projects, and research on how to raise public and private capital.
• Sustainable finance: strategies, taxonomies and supervision tools for central banks and regulators.
• Climate data and digital tools: data platforms, dashboards, remote sensing and decision-support tools.
• Agriculture, nature and resilience: climate-smart agriculture, natural capital and ecosystem analysis.
• Evaluation and capacity building: results frameworks, programme evaluations and training for government and partner staff.

What you will do:

• Process and analyse Earth observation data, both optical and radar, to track change in land cover, forests, coastlines, cropland and air quality.
• Build spatial models and indicators, such as land degradation, erosion risk or flood exposure, that feed directly into client findings and recommendations.
• Automate geospatial workflows in Python and Google Earth Engine so that analysis can be repeated reliably across countries and years.
• Design, clean and manage spatial databases, and share results through web maps, dashboards and geoportals that clients and partners can use on their own.
• Plan and support field data collection with mobile tools, and link survey results to spatial analysis.
• Apply machine learning to imagery where it adds value, for example to classify land use or detect objects.
• Turn analysis into clear maps, charts and short written narratives for reports and client presentations.
• Train client and partner staff to use and maintain the tools and data we hand over.

What success looks like in your first year:

• You have delivered the geospatial analysis for several client projects, and your maps and findings appear in final reports.
• You have built at least one documented, automated workflow that colleagues reuse on new projects.
• A client or partner team is using a web map, dashboard or geoportal you helped set up, without needing our help day to day.
• You have run at least one training session that left client staff able to update and use their own spatial data.

Requirements

Essential requirements:

If you meet these, we want to hear from you.

• A degree in GIS, geospatial information science, remote sensing, geography, environmental science or a related field.
• Working fluency in QGIS or ArcGIS, and in Python for geoprocessing and automation.
• Experience of multi-temporal analysis in Google Earth Engine or a similar cloud platform.
• The ability to explain technical results clearly, in writing and in person, to people who are not GIS specialists.
• The legal right to work in South Africa or Kenya.

Preferred requirements:

These are a bonus. They can also be learnt on the job.

• Experience with web GIS and spatial databases, such as PostGIS, GeoServer or GeoNode, and OGC services (WMS, WFS).
• Machine learning for imagery (for example object detection or image classification), and building simple APIs to serve models or workflows.
• Analysis of radar (SAR) imagery, such as Sentinel-1.
• Work on climate or landscape based sectors in Africa.
• Basic experience designing training materials and building the capacity of clients.
• Mobile data collection tools such as KoBoToolbox.

Who you are:

• Curious about how places change and committed to using that knowledge for positive impact.
• Collaborative: you enjoy working with consultants, clients and field teams, and you share what you know.
• Careful with data: you document your work so that others can check and repeat it.
• Adaptable and growth-oriented: you pick up new tools and methods as projects need them.

What's in it for you: the Genesis deal

• Meaningful work: your analysis will inform real decisions by governments, development finance institutions and donors.
• Talented colleagues: you will work in teams where everyone plays a part and teamwork is the norm.
• A supportive environment: our culture is dynamic, respectful and rooted in trust. You will be challenged to grow, with support at every step.
• Career development: we invest in your growth through structured feedback, skills development and clear opportunities to advance.

• Process and analyse Earth observation data, both optical and radar, to track change in land cover, forests, coastlines, cropland and air quality.
• Build spatial models and indicators, such as land degradation, erosion risk or flood exposure, that feed directly into client findings and recommendations.
• Automate geospatial workflows in Python and Google Earth Engine so that analysis can be repeated reliably across countries and years.
• Design, clean and manage spatial databases, and share results through web maps, dashboards and geoportals that clients and partners can use on their own.
• Plan and support field data collection with mobile tools, and link survey results to spatial analysis.
• Apply machine learning to imagery where it adds value, for example to classify land use or detect objects.
• Turn analysis into clear maps, charts and short written narratives for reports and client presentations.
• Train client and partner staff to use and maintain the tools and data we hand over.

• QGIS
• ArcGIS
• Python for geoprocessing and automation
• Google Earth Engine
• Multi-temporal analysis
• Web GIS
• Spatial databases
• PostGIS
• GeoServer
• GeoNode
• OGC services (WMS, WFS)
• Machine learning for imagery
• Object detection
• Image classification
• Simple APIs
• Radar (SAR) imagery analysis
• Sentinel-1
• Mobile data collection tools
• KoBoToolbox

• A degree in GIS, geospatial information science, remote sensing, geography, environmental science or a related field.
• Working fluency in QGIS or ArcGIS, and in Python for geoprocessing and automation.
• Experience of multi-temporal analysis in Google Earth Engine or a similar cloud platform.
• The ability to explain technical results clearly, in writing and in person, to people who are not GIS specialists.
• The legal right to work in South Africa or Kenya.