Senior Lidar & Geospatial Engineering Lead (Hybrid/Remote)

kbr

United States

Hybrid

USD 150,000 - 210,000

Full time

3 days ago
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Job summary

KBR's Science and Space Division seeks a Senior Lidar Systems & Geospatial Engineering Lead to provide technical leadership for lidar system characterization, QA/QC, and advanced geospatial analysis, with emphasis on large-scale airborne lidar programs such as 3DEP. The role combines algorithm development, standards support, and mentorship of a multidisciplinary team.

The candidate will develop scalable Python tools, evaluate accuracy and density, and publish results.

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.

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

Skills

Airborne Lidar
3DEP QA/QC
ASPRS Standards
Point Density & Spatial Distribution
Voronoi Analysis
Vertical Accuracy
GNSS/TLS/Total Station Validation
Point-Cloud Processing
Python Geospatial Development
PDAL/laspy/LASTools
Large-Scale Data Processing
Algorithm Development
System Characterization
Technical Leadership
Strong Communication Skills

Education

MS in physics
PhD preferred

Tools

PDAL
laspy
LASTools

Job description

KBR's Science and Space Division seeks a Senior Lidar Systems & Geospatial Engineering Lead to provide technical leadership for lidar system characterization, QA/QC, and advanced geospatial analysis, with emphasis on large-scale airborne lidar programs such as 3DEP. The role combines algorithm development, standards support, and mentorship of a multidisciplinary team.

The candidate will develop scalable Python tools, evaluate accuracy and density, and publish results.

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