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Earth Observation Data Scientist

Posted on Aug. 25, 2025 by C-CORE

  • Full Time

Earth Observation Data Scientist

At C-CORE, we are committed to investing in people and creating a dynamic and rewarding employment experience. We are seeking an Earth Observation Data Scientist to join our Earth Observation team.

About C-CORE

C-CORE conducts R&D and provides research-based advisory services, delivering innovative engineering and technology solutions to national and international clients. Over the past 50 years, we have built a world-class team of over 70 dedicated professionals with a reputation for excellence in Remote Sensing and Oceans & Energy. We are looking for exceptional individuals to join our team and contribute to our continued success, and solve challenging problems for industry and the environment for sustainable development.

Position Overview

As an Earth Observation Data Scientist at C-CORE, you will play a key role in delivering and advancing our capabilities in remote sensing, especially in land cover monitoring and GHG emissions research and development. You will work with advanced satellite technologies and methodologies to provide innovative solutions to our clients. This position offers the opportunity to work in either our St. John's, NL, or Ottawa, ON, office, and to be part of a leading-edge team dedicated to excellence in Earth Observation (EO).

Key Responsibilities

  • Design and implement AI/ML pipelines using multi-sensor EO time-series (SAR, Optical, Thermal) to support GHG monitoring and land classification.
  • Develop and apply deep learning models for image segmentation, object detection, and spatiotemporal change analysis.
  • Process, archive, and manage remote sensing datasets, ensuring accessibility and quality control.
  • Support wetland and Arctic land cover classification projects in compliance with internal standards.
  • Perform advanced spatial analysis and visualization for environmental and disaster management use cases.
  • Collaborate with project teams and external stakeholders to ensure delivery of EO products.
  • Compile technical documentation, metadata, and research proposals.
  • Contribute to the development and improvement of EO data processing systems and tools.

Desired Qualifications

  • A bachelor’s degree in Remote Sensing, Atmospheric Science, Computer Science, Physics, or related discipline is required. A Master’s or Ph.D. is preferred, with an exposure to Remote Sensing, Machine Learning, or Geographic Information Systems (GIS).
  • Proficiency in remote sensing data processing and analysis techniques.
  • Knowledge of remote sensing principles, SAR and optical data processing, geospatial AI techniques, and GHG monitoring.
  • Skills in Python programming, statistical modeling, ML frameworks (e.g., PyTorch, TensorFlow), and cloud platforms (AWS/GCP).
  • Experience with geospatial data (e.g., digital air photos, Earth Observation imagery).
  • Attention to detail and willingness to work in multiple areas.
  • Excellent written and oral English communication skills.
  • Capable of independent research, cross-functional collaboration, mentoring, proposal writing, and solution-driven problem-solving.
  • Must be a Canadian resident with a valid work authorization.

Salary & Benefits

C-CORE offers competitive salaries and benefits, including attractive vacation entitlements and comprehensive medical and dental plans. We are committed to professional development, higher education, and personal growth.

Deadline for Submission

September 8, 2025

How to Apply

Please forward your résumé electronically to: careers@c-core.ca, stating "EO Data Scientist" in the subject line.

C-CORE thanks all applicants; however, only those selected for an interview will be contacted.

Job Type: Full-time

Pay: From $80,000.00 per year

Benefits:

  • Company events
  • Dental care
  • Employee assistance program
  • Extended health care
  • On-site parking
  • Paid time off
  • RRSP match
  • Tuition reimbursement

Work Location: In person


Advertised until:
Sept. 24, 2025


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