Data Scientist IV

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Battelle’s National Security Business Unit is seeking experienced Geospatial Researchers/Data Scientists to support cutting‑edge research and development activities for the Army Geospatial Center and ERDC’s Geospatial Research Laboratory. This remote position supports client activities voir, VA and offers a comprehensive benefits package including health, dental, vision, life insurance, 401(k), pension plan, and tuition reimbursement.

The primary deliverable is the development of well‑formed, 3D urban‑relevant models that are effective for operational applications and exhibit smart reduction techniques, enabling sharing in low‑bandwidth environments. Models must be optimized for use in Army tactical systems, with priority on rapid development timelines, minimized file sizes, and high utility in operational contexts.

• Review scientific literature to identify and implement appropriate research methods.
• Extract, organize, and analyze data from diverse databases and files at varying scales.
• Develop software tools utilizing statistical and machine‑learning techniques.
• Critically evaluate data for completeness, accuracy, and applicability.
• Communicate technical results clearly, emphasizing data visualization.
• Collaborate effectively with co‑located and geographically diverse team members.
• Author and contribute to technical reports and presentations, including tables, graphs, and software tools.
• Implement methodologies to solve complex geospatial problems.
• Develop and optimize 3D urban models for operational use, focusing on smart reduction for low‑bandwidth sharing and integration with Army tactical systems.

• Experience/knowledge in photogrammetry and remote sensing.
• Coding expertise (Python preferred), with a focus on open‑source software.
• Experience collecting and processing point‑cloud data from LiDAR and EO sensor systems (aerial, terrestrial, mobile).
• Proficiency with 3D data visualization/manipulation software (ArcGIS Pro, QGIS, Cloud Compare, QT Modeler, Meshlab, Agisoft Metashape, Reality Capture, Blender, Unreal, Unity).
• Familiarity with 3D mesh generation and texturing (OBJ, glTF formats).
• Expertise in data compression for efficient 3D model storage and dissemination.
• Experience with real‑time 3D rendering and optimization for low‑power devices.
• Familiarity with US Army geospatial end‑user devices (e.g., ATAK, GWS).
• Knowledge of machine learning for automated feature extraction and model simplification (3D data models).
• Understanding of geospatial data standards for interoperability.
• Field‑work experience in geospatial data collection, testing, and evaluation.
• Understanding of geodetic principles, 3D/2D registration, and georeferencing.
• Experience with survey control data collection, post‑processing, and product generation (GPS, Total Station).

• Inherently curious, innovative, and a natural problem solver.
• Ability to design and complete R&D projects.
• Experience working as a team member and team leader.
• Strong communication skills for presenting complex technical concepts to non‑technical stakeholders.
• Adaptability to rapidly evolving technologies and operational requirements.
• Publishing experience in peer‑reviewed journals or strong technical writing skills.
• Statistical data analysis skills (preferred).

• Existing or eligible to obtain TS/SCI clearance.
• Ideally local to Northern Virginia area (remote candidates considered).
• Senior‑level experience (not junior; able to be productive quickly).
• Military/Army/DoD background highly beneficial (especially familiarity with fielded systems and use‑cases).

• Compressed work schedule:
  Most of our team follows a flexible, compressed work schedule that allows for every other Friday off.
• Hybrid arrangement:
  Work 60% in‑office, 40% remote, with Monday and Tuesday as common in‑office days, dependent on team and position needs.
• Paid time off to support work‑life balance and keep motivated.
• Medical, dental, and vision coverage with wellness incentives and benefits plus a variety of optional supplemental…