Andie Williams

About Andie Williams

Executive SummaryPrincipal Data & AI Architect — focused on making probabilistic systems operationally reliable.Why This Matters I’m a Principal Data & AI Architect. Most of my career has been spent taking messy, high-risk decision environments — finance, healthcare, fraud, regulated systems — and turning them into architectures organizations can safely depend on.I’m not a model researcher and I’m not just a data engineer — I sit between business decisions and technical uncertainty. My job is making sure analytics and AI outputs are reliable enough to run operations and not just dashboards.At HP I designed the data architecture behind a $500M SaaS telemetry platform (TechPulse) for which I was awarded 6 US Patents, at Toyota Financial I built regulatory risk analytics, and recently at Booz Allen I’ve been shaping fraud and healthcare decision platforms under federal compliance constraints.The common thread is governance and reliability — grounding probabilistic systems in deterministic workflows so organizations can trust automated decisions. That’s really the work I focus on.

Experience

1. Principal Data and Ai Architect

   Booz Allen Hamilton

   Apr 2023 — Present

   Principal Data (AI) Architect for NIH & VA GameChanger, designing AI-driven knowledge discovery platforms enabling senior defense leaders to search, synthesize, and operationalize policy and intelligence at scale. • Architected large-scale document ingestion, NLP, and semantic search pipelines supporting secure analysis across classified and open-source corpora. • Served as Principal Architect for CDC DMAC viral surveillance systems, designing population-scale data platforms for real-time epidemiological monitoring and public-health decision support. • Built high-throughput, multi-source data ingestion and normalization architectures supporting modeling, forecasting, and outbreak response. • Led architecture for CMS ACA fraud detection platforms, protecting multi-billion-dollar federal healthcare programs through advanced analytics and ML-driven risk scoring. • Designed anomaly detection and fraud-prediction pipelines processing massive claims datasets to identify fraud, waste, and abuse. • Established federal-grade security, privacy, and compliance architectures across all platforms, ensuring auditability, data integrity, and regulatory alignment. • Provided technical governance and architectural leadership across data science, engineering, and DevOps teams, aligning mission outcomes with scalable cloud and big-data architectures.

Education

• Loyola Marymount University

  Bachelor of Arts (B.A.), Theology/Theological Studies

  1991 — 1994

Skills

• Leadership
• Cloud Computing
• Analytics
• Financial Analysis
• Sql
• Data Analysis
• Big Data
• Vendor Management
• Tableau
• Databases
• Kaizen
• Management
• Consulting
• IT Strategy
• Sdlc
• Program Management
• Software Development
• Strategy
• Business Intelligence