Andrew Moore

AI Engineer @ Divergent 3D | AI Engineer & Data Scientist | Ex-NASA, U.S. Department of Homeland Security | Generative AI and Data-Driven Solutions

Role
Data Scientist at Booz Allen Hamilton
Location
Los Angeles, CA, US
LinkedIn followers
500 followers
Information TechnologyView LinkedIn profile

About Andrew Moore

AI Engineer and Data Scientist with experience supporting large-scale NASA missions (including Mars Sample Return) and U.S. Department of Homeland Security initiatives. Skilled in machine learning, generative AI, and cloud computing. Focused on enhancing operational efficiency and solving complex problems through data-driven solutions.

Experience

  1. Data Scientist

    Booz Allen Hamilton

    Jul 2024 — Present · Los Angeles, CA, US

    Developed a high-speed document similarity agent for NASA and Department of Defense (DoD) clients as part of MAPPy, a generative AI web app for Systems Engineers—enabling comparison of documents in under 30 seconds and contributing directly to a $1M sale• Orchestrated a high-performance data pipeline that ingested tens of thousands of system requirements into MAPPy within seconds, and developed a requirement verification AI agent with 95% accuracy—making MAPPy the first generative AI tool to integrate with the IBM DOORS platform and enabling streamlined validation of highly complex requirements• Driving end-to-end development of a high-volume data pipeline that ingests over 100 GB of operational and financial data daily—powering an executive dashboard used by Booz Allen’s C-suite for strategic decision-making on a $1B account• Engineered a full-stack web application to predict satellite collision risks within 48 hours (1–3 km accuracy), combining physics-based modeling with a generative AI (RAG) pipeline powered by Amazon Bedrock—deployed on AWS EC2 and integrated into internal operations

Education

  • University of Southern California

    Bachelor of Science - BS

    2019 — 2022

  • University of Southern California

    Master of Science - MS

    2021 — 2023

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