We are looking for an ecologist who codes. You will turn ecological theory and field data into models, tools and evidence that shape infrastructure, nature-based solutions (NbS) and natural capital decisions across Singapore and Asia-Pacific.
AECOM's Singapore Biodiversity team delivers Environmental Impact Assessment (EIA), NbS design, natural capital and biodiversity accounting, ecological restoration and nature-related advisory aligned with frameworks such as TNFD, SEEA EA and IFC PS6. This role builds the team's quantitative and digital capability.
You will understand why ecosystems behave as they do: population and community dynamics, landscape ecology, connectivity, succession and ecosystem function. You will also have the coding and AI skills to test those ideas against real data at scale.
A balance of biodiversity related field work will be required for this role:
Spatial ecology and modelling
- Build and validate species distribution, habitat suitability and ecological connectivity models to inform EIA, corridor design and NbS siting.
- Apply ecological theory to model design: choose predictors, scales and assumptions that reflect real ecosystem processes, and communicate uncertainty clearly.
- Produce reproducible spatial analyses and map outputs in Python, R and GIS.
Natural capital and biodiversity accounting
- Develop analytical workflows for ecosystem extent and condition accounts, biodiversity metrics and indicators aligned with SEEA EA, TNFD and related frameworks.
- Translate ecological data into metrics that clients, financiers and regulators can use for disclosure, investment and planning decisions.
Field data systems and survey pipelines
- Design and deploy field data collection applications that streamline data capture and reduce transcription and QA effort.
- Build and manage project and team databases for biodiversity survey data, including schema design, data standards, version control and access.
- Automate survey data pipelines: species list validation against reference databases, conservation status flagging, and processing of camera trap and bioacoustic outputs.
AI and automation
- Train and evaluate machine learning models, and apply pre-trained ecological AI tools (e.g. BirdNET, MegaDetector) with appropriate validation.
- Build LLM-assisted workflows for reporting, QA and data extraction, and use AI coding assistants productively and critically.
- Champion good practice in reproducible code, documentation and responsible AI use across the team.
Project delivery
- Write technical report sections and appendices for EIA, NbS and natural capital deliverables.
- Present analytical findings in client and regulator meetings, including with NParks and other agencies.
- Support field surveys where needed to understand data collection, test tools and maintain ecological grounding, whilst contributing to overall project requirements.