Financial Engineering · AI-Native Data Systems · Event-Driven Research
Nicholas Wagner
I build research infrastructure for turning messy public information—filings, central-bank communications,
market data, and technical documents—into structured signals, dashboards, and decision-support systems.
An independent public-data BI demonstration for the Lehigh County Authority context:
compare five-year water and wastewater rate scenarios across three divisions, customer bills, capital funding, and financial resilience.
Interactive 2027–2031 rate planning and constrained scenario search
Transparent source reconciliation, assumptions, and agreement boundaries
Stress tests, synthetic ERP validation, and reusable analyst guides
Controlled Claude Code backend/model evaluation on Terminal-Bench/Harbor with repeated full-suite trials,
provider-aware cost reconciliation, provenance review, and trajectory/failure analysis.
LLM-assisted pipeline for acquiring Federal Reserve communications, generating structured monetary-policy
sentiment scores, and visualizing sparse, irregular central-bank communication signals for portfolio research.
FOMC release scraping and normalization
OpenAI Batch API scoring jobs
Structured score families for rates, inflation, employment, credit, growth, surprise, and policy phase
SolidJS/ECharts dashboard for sponsor-facing analysis
Local-first SEC filing infrastructure for turning filings, exhibits, and event disclosures into reproducible
research artifacts and structured event signals.
py-sec-edgar-m and SEC/EDGAR ingestion workflows
Deterministic document identities
Raw and parsed artifact tracking
Event extraction and downstream research workflows
AI-Native Event-Driven Hedge Fund Research OS
Prototype architecture for agent-assisted investment research: ingest documents, extract structured events,
generate trade hypotheses, run backtests, and write experiment postmortems.
Filing-to-event extraction
Trade-candidate generation
Backtest and attribution workflow
Reflection/postmortem agent design
The Wagner Valkyries Project
Fan-augmented ground-effect vehicle concept designed as a physical platform for validating controllable
downforce, active chassis control, and force-aware vehicle-system IP.
Engineering Mindset Across Software and Physical Systems
My work sits at the intersection of financial engineering, software systems, and physical prototyping. Before
focusing on AI-native finance and data infrastructure, I co-founded Opentrons Labworks and helped build early
liquid-handling robotics systems, including firmware and Python API work for the OT-1.
That builder background now informs my approach to research systems: make the pipeline observable,
reproducible, and useful enough that others can test and extend it.
Published Materials
Documents
Resume
Canonical web resume with cleaned public-facing content.
A sponsor-facing technical report covering Federal Reserve communication scoring, FOMC ingestion, OpenAI
Batch API processing, score materialization, visualization, limitations, and continuation recommendations.
