David L
Managing Director at Accenture Federal Services
Virginia, United States
Summary
👤
Senior🎓
Top SchoolDavid L is a Managing Director and seasoned technology leader with 11 years of experience specializing in MLOps, computer vision, and large-scale data engineering across cloud platforms (AWS, Azure, GCP). He has driven solution architecture and delivery for complex geospatial and remote sensing systems, blending domain expertise in Python, ArcGIS/QGIS, and OpenGEO tooling with practical performance and systems testing. At Accenture Federal Services he progressed from Applied Intelligence Senior Manager to Managing Director, leading machine learning and data science innovation for federal clients. His background includes principal engineering work at In-Q-Tel and ISR-focused systems engineering at BAE, giving him uncommon depth in operationalizing AI for intelligence and defense contexts. David pairs rigorous aerospace and geospatial academic training with hands-on implementation experience, making him adept at turning research-grade models into resilient, production-ready systems.
11 years of coding experience
12 years of employment as a software developer
AB Engineering Sciences, AB Engineering Sciences at Dartmouth CollegeMaster of Science (M.S.) Aerospace Aeronautical and Astronautical Engineering, Master of Science (M.S.) Aerospace Aeronautical and Astronautical Engineering at University of Southern CaliforniaBachelor of Engineering concentrating Mechanical Engineering, Bachelor of Engineering concentrating Mechanical Engineering at Thayer School of Engineering at Dartmouth CollegeGraduate Certificate in GEOSPATIAL INTELLIGENCE ANALYTICS Geography, Graduate Certificate in GEOSPATIAL INTELLIGENCE ANALYTICS Geography at Penn State World CampusPaul D. Schrieber
Github Skills (62)
preprocessing10
corpus10
spacex10
detector10
imagery10
satellite10
satellite-imagery9
space8
machine-learning-algorithms8
machine-learning8
datasets8
searchable7
aws7
deep-learning7
python7
Programming languages (8)
Github contributions (5)
SpaceNetChallenge/SpaceNetChallenge.github.io
Sep 2017 - Nov 2018
Contributions:106 PRs, 80 pushes, 72 branches in 1 year 1 month
dlindenbaum/utilities
Mar 2017 - Oct 2018
Packages intended to assist in the preprocessing of SpaceNet satellite imagery data corpus to a format that is consumable by machine learning algorithms.
Contributions:6 PRs, 136 pushes, 82 branches in 1 year 7 months
satellite-imagerysatellitemachine-learning-algorithmscorpuscorpus-data
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