Work
Applied ML
Clayco · $8B design-build firm · 2023–2025
Receivables forecasting
Hundreds of millions in open invoices scored daily, median error 13 days
Ensemble of XGBoost and survival analysis predicting invoice payment timing, scoring tens of thousands of invoices across two years of daily batch runs. Dollar-weighted MAE of ~20 days, well inside the natural spread in collection times. Replaced a manual process that consumed hours of skilled financial analysts' time each cycle. Migrated the full train/score/monitor pipeline from Dataiku to containerized AWS: Docker images on ECR, scheduled ECS Fargate tasks, IAM scoping, Secrets Manager credential injection, CloudWatch logging with drift alerting. MLflow experiment tracking for model selection and rolling accuracy monitoring.
XGBoost · survival analysis · MLflow · Snowflake · Docker · ECR · ECS Fargate · IAM · CloudWatchread the case study→Injury-risk model
Six figures of SHAP explanations served to safety staff and site leaders
Weekly incident-probability predictions on active construction job sites with per-prediction SHAP factor decompositions stored alongside every score. Explainability-first design: the interface surfaces which features drove each site's risk so field safety teams can act on specific factors rather than an opaque number. Same containerized MLOps path (ECR/ECS/Fargate) as the forecasting system.
XGBoost · SHAP · ECS Fargate · SnowflakeEnterprise AI Platform
Human Agency · 2025–present
Data layer, security, and product discovery
40+ governed dynamic tables serving over a thousand employees across hundreds of projects
Owned the data layer for an enterprise AI platform, coordinating deeply with the client's data engineering team to integrate sources across a fractured landscape of ERPs, project management tools, HR systems, and manually maintained spreadsheets. Designed the OAuth security model that passed client security review, moving the access boundary out of application code and into the warehouse. Led product discovery for client operation use cases that were later integrated into the platform.
Snowflake · Entra/Okta OAuth · product discoveryread the case study→AI adoption module
Usage reporting across a thousand-plus weekly active users and hundreds of custom GPTs
The client rolled out Claude, ChatGPT, Copilot, and Otter to a workforce of several thousand. Reporting was manual exports and hard-coded spreadsheets. I built the governed data layer that replaced it: coordinated cross-team ingestion into Snowflake, prototyped the pipelines, and made the product decisions on metrics and rollup structure for the dashboard.
Snowflake · dynamic tables · API ingestionread the case study→Product and Agent Work
Human Agency · 2025–present
Agent plugin marketplace
Two marketplaces (52 internal skills, 5 client-facing), phased rollout across two companies
Designed and built the agent skills program end-to-end: two versioned marketplaces (one for the internal team, one executive-focused for the client's several-thousand-person org), a release pipeline with CI, and a QA process gating each skill on real-data validation before client deployment. Authored domain intelligence skills spanning finance, safety, sales, precon, recruiting, quality, and operations. Built the daily-brief family (morning intelligence digests) and subsidiary-specific variants (competitor intel, deal briefs). Designed the phased rollout strategy: internal adoption first with NPS gates, then client rollout coordinated with existing training programs. Ported skills across platforms (Claude CoWork, ChatGPT) to maximize reach across the org.
Claude · ChatGPT · Snowflake semantic views · CI/CD · GitHubExecutive agent deployments
Personal AI agents for the client's founder/chairman and CEO
Deployed and administered dedicated agent instances on AWS: ECR image management, Cloudflare tunnel routing, VNC-gated access, instance hardening. Ongoing administration including version upgrades and security patches.
AWS ECR · Docker · Cloudflare · security hardeningProduct discovery
Multiple use cases from field feedback to platform roadmap
Led product discovery for construction operations use cases, balancing off-the-shelf AI tools (ChatGPT Actions, custom GPTs) with custom-built backends to optimize time-to-value. Use cases included scope-of-work drafting and first-pass review using company standards as a knowledge base, architecture cost engineering comparison (tracking price drivers between estimate stages), and a preconstruction subcontractor module (validated data coverage across the project portfolio, coordinated with the data engineering team on the subcontractor data layer). Built RAG backends where off-the-shelf tools fell short, iterated from live field pilot feedback with PMs and project directors.
FastAPI · RAG · OpenAI vector search · GPT Actions · Snowflake