Remote Data Science Intern — GIS & Remote Sensing

DiscoverEE; Toronto; Hybrid; CAD 28,000 - 33,000; Full time

Benefits offered by this job

Health benefits

Equity pool

Two weeks vacation

Hybrid work (80% remote)

Job summary

Korotu Technology is seeking a Data Science Co-op to tackle complex, multi-modal environmental data and help advance our Aroa platform. You will work with satellite imagery, LiDAR, and field data to answer critical questions about carbon storage, habitat prioritization, and wetland health.

You will build ML models, perform geospatial analysis, and deliver data-driven insights to clients with maps and dashboards, while collaborating with a small, mission-driven team in a hybrid work setup.

Qualifications

• Bachelor’s/Master’s/PhD in a quantitative field with GIS/remote sensing coursework
• Proficiency with desktop GIS software (QGIS/ArcGIS) for spatial analysis
• Solid geospatial data foundations (raster/vector, GIS concepts)
• Strong Python for data analysis (Pandas, NumPy)
• Understanding statistics and ML concepts (hypothesis testing, regression, classification)
• Ability to conduct independent research and explain technical concepts

Responsibilities

• Solve end-to-end client challenges from brief to delivery with data-driven solutions
• Wrangle, clean, and prepare diverse geospatial datasets; perform EDA and feature engineering
• Design and train ML models to classify land cover, measure biomass, predict environmental changes
• Build scalable features for the core Aroa platform and productize repeatable workflows
• Communicate findings to clients via maps, dashboards, and compelling stories

Skills

Python

Pandas

NumPy

GIS

QGIS

ArcGIS

PostGIS

GDAL/Rasterio

Machine learning

Data wrangling

Education

Bachelor’s/Master’s/PhD in Geomatics/Math/Statistics/CS

Tools

Jupyter Notebooks

Git

Docker

Job description

Korotu Technology is seeking a Data Science Co-op to tackle complex, multi-modal environmental data and help advance our Aroa platform. You will work with satellite imagery, LiDAR, and field data to answer critical questions about carbon storage, habitat prioritization, and wetland health.

You will build ML models, perform geospatial analysis, and deliver data-driven insights to clients with maps and dashboards, while collaborating with a small, mission-driven team in a hybrid work setup.