Lead Ecologist

BNGAI™ is a Nature Intelligence Platform that uses satellite imagery and AI to deliver scalable, high quality environmental insights on any piece of land, anywhere. The platform automates habitat mapping, land classification, condition assessment, and environmental reporting at a speed and scale that manual methods cannot match.  BNGAI™ is the platform’s flagship product for the UK market, purpose built for Biodiversity Net Gain (BNG) compliance in England. BNG is one of several use cases the platform supports globally, including TNFD reporting, science based targets for nature, ESG disclosure, and large scale environmental monitoring. 

The Role 

We are looking for an experienced Lead Ecologist to lead a growing team of ecologists working on large-scale habitat mapping, field survey, and biodiversity monitoring projects across multiple clients in the UK, EU, and other regions. This role goes beyond traditional ecology management — it sits at the intersection of ecology, AI, and technology. You will combine ecological expertise, spatial data interpretation, and a strong technology orientation to help evolve AiDASH's AI-assisted mapping workflows. You'll work alongside Product and Data Science teams to shape and validate agentic-AI and RAG-based ecological workflows through intuitive, UI-based tools — no engineering background required, but a genuine appetite to learn and influence how these systems develop. You'll oversee multiple project pods, act as a team lead for a growing group of ecologists, mentor Associate Ecologists, and serve as the senior technical point of contact for ecological deliverables.at  

How You’ll Make an Impact 

Leadership & Delivery Oversight 

• Lead and manage a team of ecologists and analysts delivering habitat mapping, BNG assessments, and QA/QC across multiple client projects. 

• Ensure outputs adhere to UK BNG, DEFRA, and Natural England guidance, as well as regional biodiversity frameworks. 

• Coordinate with Project Management, Product, and Engineering to ensure timely, high-quality delivery. 

• Serve as the key technical and managerial point of contact for ecological deliverables. 

Quality & Methodology Development 

• Support the development and implementation of QA/QC frameworks for habitat mapping and classification. 

• Work with Data Science and Product teams to evolve AI-assisted and agentic mapping pipelines. 

• Introduce structured processes for testing and validating logic flows within our UI-based ecological toolchain. 

• Contribute to the improvement of SOPs, methodologies, and internal ecology training programs. 

Mentorship & Capability Building 

• Coach and mentor Associate Ecologists on ecological mapping, data validation, and logic-based tool usage. 

• Contribute to performance management, competency development, and role progression within the Ecolab team. 

Cross-functional Collaboration 

• Collaborate with GIS, Remote Sensing, and Product teams to validate ecological and AI-driven outputs. 

• Provide domain expertise during client reviews, audits, and scientific validations. 

What We’re Looking For 

• Master’s or equivalent degree in Ecology, Environmental Science, Forestry, Botany, Zoology, or a related field. 

• 7+ years of experience in applied ecology, habitat mapping, or biodiversity monitoring, including team or project leadership. 

• Proven exposure to at least two geographies (e.g., UK, EU, US, or others). 

• Deep understanding of UKHab, DEFRA metric, and BNG workflows. 

• Strong familiarity with GIS tools (QGIS, ArcGIS) and remote-sensing interpretation. 

• Tech-savvy mindset — ability to conceptualize ecological workflows, build and test logic flows, and collaborate with AI/engineering teams to refine agentic systems. 

• Excellent leadership, coaching, and communication skills. 

Why AiDASH

• Join a global team driving innovation at the intersection of ecology, AI, and climate resilience. 

• Work with leading utilities, developers, and consultancies across multiple regions. 

• Shape the next generation of digital ecology and AI-enabled biodiversity intelligence.