Senior Software Engineer & Designer developing software architecture for forestry LiDAR data at Forsite. Collaborating with specialists and mentoring team members on best practices.
Responsibilities
Design and develop software architecture and processing pipeline components for forestry LiDAR data, including systems built in Python, Rust, and JavaScript
Lead the design of scalable, maintainable data processing workflows for large-volume point cloud and natural resource datasets
Perform data analysis and develop statistical models for R&D projects related to LiDAR point cloud processing and other natural resource datasets
Evaluate emerging methodologies and advance the current state of the science in LiDAR-based natural resource assessments
Contribute to the preparation, authorship, and peer review of scientific and technical publications in remote sensing and related disciplines
Conduct code reviews and maintain code quality standards across the analytics and GTC teams
Work collaboratively with forestry specialists, data scientists, and project managers to integrate software solutions into operational workflows
Provide technical guidance and mentorship to team members on software development best practices and analytical methods
Requirements
Master's degree or PhD in Computer Science, Geomatics, Remote Sensing, Applied Mathematics, Forestry, or a closely related discipline
Demonstrated experience in software development and system design, with advanced proficiency in Python and at least one compiled language (Rust, C++, or equivalent)
Demonstrated experience in statistical modelling and quantitative data analysis applied to large, complex spatial or point cloud datasets
Experience with LiDAR data processing, remote sensing analysis, or natural resource data pipelines
Track record of authorship or substantive contribution to peer-reviewed or professional technical publications
Experience conducting code reviews in a collaborative development environment
Proficiency with version control systems (Git)
Nice to have: Experience with forestry inventory methods, airborne LiDAR acquisition, or related natural resource remote sensing applications
Familiarity with point cloud libraries and geospatial data formats (e.g., LAS/LAZ, GeoTIFF, Shapefile)
Experience with high-performance or distributed computing environments
Experience in an applied research or industry-academia collaborative setting
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