Ecologist & Data Scientist — Spatial AI

AECOM; Singapore; Hybrid; SGD 120,000 - 180,000; Full time

Job summary

AECOM is seeking an ecologist who codes to turn ecological theory and field data into models, tools and evidence that shape infrastructure, nature-based solutions and natural capital decisions across Singapore and Asia-Pacific.

You will help build the team’s quantitative and digital capability, applying population and landscape ecology, connectivity and ecosystem function while coding in Python and R to test ideas against real data at scale.

Qualifications

• Bachelor's degree or higher in ecology, conservation biology, environmental science, or related field.
• Strong grounding in ecological theory and ecosystem dynamics.
• Strong coding in Python and/or R with data wrangling and spatial analysis.
• Experience with machine learning and AI, including AI-assisted coding and LLM tools.
• Experience with field data capture apps or digital survey workflows.
• Working GIS proficiency (e.g. ArcGIS Pro, QGIS) and data standards.

Responsibilities

• Build and validate species distribution, habitat suitability and ecological connectivity models to inform EIA and NbS siting.
• Develop analytics for ecosystem extent/condition and biodiversity metrics aligned with SEEA EA, TNFD.
• Design and deploy field data collection applications and manage biodiversity survey databases.
• Train and evaluate machine learning models and apply AI tools with proper validation.
• Prepare technical report sections and present findings to clients/regulators.

Skills

Python programming

R programming

Machine learning

Data wrangling

English proficiency

Education

Bachelor's degree in ecology, conservation biology, environmental science, biology or related field

Tools

ArcGIS Pro

QGIS

Google Earth Engine

Git

Shiny

Streamlit

Job description

AECOM is seeking an ecologist who codes to turn ecological theory and field data into models, tools and evidence that shape infrastructure, nature-based solutions and natural capital decisions across Singapore and Asia-Pacific.

You will help build the team’s quantitative and digital capability, applying population and landscape ecology, connectivity and ecosystem function while coding in Python and R to test ideas against real data at scale.