Environmental Data Scientist (Biodiversity)

About the role

AECOM's Singapore Biodiversity team is looking for an ecologist who codes. The role turns 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. It builds the team's quantitative and digital capability, within a scope covering 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.

Key responsibilities

• Spatial ecology and modelling: build and validate species distribution, habitat suitability and ecological connectivity models, and produce reproducible spatial analyses and maps 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
• Field data systems: design and deploy field data collection apps, manage biodiversity survey databases and automate survey pipelines (species validation, conservation status flagging, camera trap and bioacoustic processing)
• AI and automation: train and evaluate machine learning models, apply pre-trained ecological AI tools (e.g. BirdNET, MegaDetector), and champion reproducible code and responsible AI use
• Project delivery: write technical report sections and appendices for EIA, NbS and natural capital deliverables, present findings to clients and regulators (including NParks), and support field surveys

Required profile

• Bachelor's degree or higher in ecology, conservation biology, environmental science, biology or a related field, supported by a portfolio of analytical or coding work
• Strong grounding in ecological theory and ecosystem dynamics
• Experience designing or managing structured datasets or databases, and with field data capture apps or digital survey workflows
• Clear written and spoken English, and willingness to join fieldwork in tropical conditions

Required skills

• Python and/or R, including data wrangling, statistical modelling and spatial analysis
• Hands-on machine learning and AI experience, and working GIS (ArcGIS Pro, QGIS or spatial libraries in Python/R)
• Desirable: flora/fauna survey and identification, remote sensing (Google Earth Engine, Sentinel, Landsat, drones), connectivity tools, camera trap/bioacoustic/eDNA processing, app development (Shiny, Streamlit), Git, and prior consultancy experience in Southeast Asia