Senior Lidar Systems & Geospatial Engineering Lead
KBR
- Location
- Sioux Falls, South Dakota
- Work model
- On-Site
- Level
- Senior
- Posted
- Aug 21, 2026
Skills
About this role
Title: Senior Lidar Systems & Geospatial Engineering Lead BELONG. CONNECT. GROW. with KBR. Around here, we define the future. We are a company of innovators, thinkers, creators, explorers, volunteers, and dreamers. But we all share one goal: to improve the world responsibly and safely. KBR’s Science and Space Division is seeking a Senior Lidar Systems & Geospatial Engineering Lead to support the USGS Earth Resources Observation and Science (EROS) Center’s EROS Calibration/Validation Center of Excellence (ECCOE) project. This is a full-time, specialized position that provides technical leadership for lidar system characterization, quality assurance, accuracy assessment, and advanced geospatial analysis, with emphasis on large-scale airborne lidar programs such as the USGS managed 3D Elevation Program (3DEP). The role combines lidar subject-matter expertise, algorithm and software development, standards support, and technical leadership to develop rigorous, scalable methods for evaluating point-cloud quality, density, spatial consistency, and elevation accuracy. The Senior Lidar Systems & Geospatial Engineering Lead will write and publish results for peer-reviewed publications and actively participate in professional organizations, conferences, and workshops.
Core Responsibilities
Lead technical QA/QC and characterization of airborne lidar datasets and derived elevation products against 3DEP, ASPRS, contractual, and project-specific requirements. Develop and implement advanced methods for evaluating lidar point density, spatial distribution, completeness, and localized deficiencies, including point-based and Voronoi-based density approaches. Perform vertical accuracy assessments using GNSS, total-station, terrestrial laser scanning, UAS, and other independent reference datasets; evaluate bias, RMSE, variability, and spatial error patterns and metrics. Investigate lidar anomalies and determine whether observed deficiencies are associated with acquisition, calibration, classification, processing, or product-generation workflows. Develop scalable Python-based tools for processing tens of millions of points per tile and thousands of production datasets using libraries such as NumPy, SciPy, GeoPandas, Shapely, PDAL, laspy, and Rasterio. Design automated QA/QC workflows, acceptance metrics, statistical summaries, density histograms, spatial deficiency maps, and project-level exception reporting. Conduct applied research to improve lidar quality metrics and evaluate limitations of conventional raster-based density and accuracy assessment methods. Perform sensitivity analyses addressing point-return selection, edge effects, spatial resolution, density thresholds, and algorithm configuration. Support development and interpretation of ASPRS lidar density and positional accuracy standards and related industry guidance. Evaluate emerging airborne, terrestrial, UAS, and spaceborne lidar technologies and their potential application to national-scale 3D mapping programs. Provide technical review of methodologies, specifications, statements of work, contractor deliverables, and research products. Lead and mentor multidisciplinary teams of scientists, engineers, analysts, and software developers and communicate complex technical findings to program managers, government stakeholders, industry partners, and researchers. Work with USGS representatives at EROS and the National Geospatial Technical Operations Center (NGTOC) to incorporate lidar data quality products and processes into standards and specifications. Support ECCOE System Characterization team with commercial data quality analysis Qualifications Minimum of MS in physics, mathematics, remote sensing, geospatial science, geomatics, environmental science, or a related field; PhD preferred 8+ years of progressive, lidar-related experience Fundamental programming skills Desired Skills Airborne Lidar 3DEP QA/QC ASPRS Standards Point Density & Spatial Distribution Voronoi Analysis