GIS Data Scientist (AWS / AI / Geospatial Analytics) (SG Citizen/PR only, 1 Year Contract)

GIS Data Scientist (AWS / AI / Geospatial Analytics)

We are looking for a hands-on GIS Data Scientist to design, build, and deploy scalable AI and data science solutions on large-scale geospatial datasets within AWS cloud environments, including government cloud ecosystems.

This role focuses on end-to-end delivery — from geospatial data processing and feature engineering to machine learning model development, backend API integration, and production deployment. You will work closely with engineering, product, and platform teams to deliver production-grade AI systems supporting spatial analytics, forecasting, and intelligent decision-making use cases.

The ideal candidate combines strong engineering fundamentals with practical AI/ML delivery experience and is comfortable operating in fast-paced, agile environments.

Key Responsibilities

Geospatial Data Processing & Analytics

• Ingest, process, and analyze large-scale geospatial datasets including vector, raster, and spatial time-series data

• Perform:

◦ Spatial feature engineering

◦ Data enrichment and transformation

◦ Geospatial statistical analysis

• Build reusable geospatial data pipelines supporting analytics and AI use cases

• Work with spatial indexing, spatial joins, and scalable spatial querying techniques

AI / Machine Learning Development

• Design, develop, and deploy machine learning and AI models for:

◦ Pattern detection

◦ Forecasting and predictive analytics

◦ Spatial and behavioral insights

• Build and optimize:

◦ Classification and regression models

◦ Geospatial ML workflows

◦ AI/NLP/Computer Vision pipelines where applicable

• Perform:

◦ Feature engineering

◦ Model tuning and evaluation

◦ Performance optimization

• Productionize AI/ML models for scalable cloud-native deployment

Backend Integration & AI Services

• Develop backend services and APIs to expose AI/ML capabilities to downstream applications

• Build and maintain:

◦ REST APIs

◦ AI microservices

◦ Backend integration services

• Integrate AI models into enterprise platforms and operational systems

• Collaborate closely with software engineering teams for production integration

Cloud & Data Platform Engineering (AWS)

• Develop and deploy AI/data solutions within AWS cloud environments

• Build scalable:

◦ Data processing pipelines

◦ ML deployment frameworks

◦ Cloud-native analytics solutions

• Work with AWS services across:

◦ Compute and container environments

◦ Data storage and processing platforms

◦ Workflow orchestration and deployment automation

• Support CI/CD and automated deployment pipelines for AI workloads

• Ensure systems are secure, scalable, maintainable, and production-ready

Cross-functional Collaboration

• Work closely with:

◦ Data Engineers

◦ Product Managers

◦ Full-stack and Frontend Engineers

◦ Platform and DevOps teams

• Contribute to:

◦ Technical design discussions

◦ Solution architecture reviews

◦ Agile sprint delivery and planning

• Translate business requirements into scalable AI and geospatial solutions

Required Skills & Experience

Core Technical Skills

• Strong hands-on programming experience in Python

• Experience with:

◦ Pandas

◦ PySpark

◦ NumPy

• Experience working with geospatial tools and frameworks such as:

◦ GeoPandas

◦ GDAL

◦ Spatial SQL / PostGIS

◦ Raster and vector processing libraries

• Strong understanding of large-scale data processing and analytics workflows

AI / ML Engineering

• Proven experience building and deploying ML models end-to-end

• Experience with machine learning libraries/frameworks such as:

◦ scikit-learn

◦ TensorFlow

◦ PyTorch

• Strong understanding of:

◦ Feature engineering

◦ Model tuning and evaluation

◦ Model deployment and productionization

• Experience integrating AI services and LLM workflows is advantageous

Cloud & Infrastructure (AWS)

• Practical experience building AI/data solutions on AWS

• Experience with:

◦ Cloud-native data pipelines

◦ Containerized deployments

◦ CI/CD pipelines

◦ Infrastructure automation

• Familiarity with:

◦ Docker

◦ Kubernetes / ECS / EKS

◦ Deployment automation workflows

Backend Development

• Experience developing backend services and APIs for AI/ML systems

• Strong understanding of:

◦ REST APIs

◦ Microservices architecture

◦ System integration patterns

• Experience integrating ML services into production applications

Good to Have

• Cleared government technical assessments or prior government project experience

• Experience with:

◦ Real-time or streaming data pipelines

◦ MLOps practices including model monitoring and versioning

◦ Spatial optimization, routing, or geospatial graph analytics

• Exposure to frontend or full-stack development such as:

◦ React

◦ Dashboard applications

• Experience working in agile, cross-functional delivery teams

• Familiarity with government cloud environments and secure delivery practices

Key Attributes

• Strong hands-on engineering mindset with a practical delivery focus

• Able to independently own and execute technical deliverables

• Comfortable working in fast-paced, iterative environments

• Strong analytical and problem-solving skills

• Able to translate business problems into scalable AI/data solutions

• Strong communication and stakeholder management skills

• Collaborative and team-oriented approach