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Senior Lidar Systems & Geospatial Engineering Lead

KBR

Senior Lidar Systems & Geospatial Engineering Lead

full-timePosted: Aug 21, 2026Updated: Sep 3, 2026South Dakota, Sioux Falls

Job Description

Title:Senior Lidar Systems & Geospatial Engineering LeadBELONG. 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 ResponsibilitiesLead 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 analysisQualificationsMinimum of MS in physics, mathematics, remote sensing, geospatial science, geomatics, environmental science, or a related field; PhD preferred8+ years of progressive, lidar-related experienceFundamental programming skillsDesired SkillsAirborne Lidar3DEP QA/QCASPRS StandardsPoint Density & Spatial DistributionVoronoi AnalysisVertical AccuracyGNSS/TLS/Total Station ValidationPoint-Cloud ProcessingDEMs & Terrain AnalysisPython Geospatial DevelopmentPDAL/laspy/LASToolsLarge-Scale Data ProcessingAlgorithm DevelopmentSystem CharacterizationTechnical LeadershipStrong Communication SkillsWork LocationThis position supports a team anchored in Sioux Falls, SD, and is offered in a hybrid remote/onsite work environment. Fully remote work will be considered for the right candidate.Three years of continuous residency in the US for issuance of a Government Security credential is required.SPECIAL REQUIREMENTSThree years of continuous residency in the US for issuance of a Government Security credentialThe candidate must be able to obtain and maintain a national agency check and background investigation after hiring to obtain a badge for government facility access and user accountExperience and/or Education in lieu of these qualifications will be reviewed for applicability to meet these requirements.KBR Benefits:​ KBR offers a selection of competitive lifestyle benefits which could include 401K plan with company match, medical, dental, vision, life insurance, AD&D, flexible spending account, disability, paid time off, or flexible work schedule. We support career advancement through professional training and development.​ Click here to learn more: KBR Benefits | KBR #LI-EM2Belong, Connect and Grow at KBRAt KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of team’s philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver – Together. KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.

Locations

  • South Dakota, Sioux Falls

Required Qualifications

  • Three years of continuous residency in the US for issuance of a Government Security credential (experience)

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

Benefits

  • general: KBR offers a selection of competitive lifestyle benefits which could include 401K plan with company match, medical, dental, vision, life insurance, AD&D, flexible spending account, disability, paid time off, or flexible work schedule. We support career advancement through professional training and development.​
  • general: Belong, Connect and Grow at KBRAt KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of team’s philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver – Together.
  • general: KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.

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