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About this paper

Who publishes it, what they trained in, what they can do, how to reach them, and how the pages are put together.

Publisher’s note

Most of what I build starts as a question I can't answer from the outside. Does owning mining equipment in this game actually pay? How many wallets on this launchpad are distinct people? The only honest way to find out is to index the chain yourself and look, so that's usually where the project starts — and the product tends to fall out of the dataset rather than the other way round.

That means I spend real time on the unglamorous half. Indexers that stay up. MongoDB collections with indexes designed for the queries that will actually run against them. Contracts with test suites that pass before anything touches mainnet. Then the interesting half: wallet clustering, emission reconstruction, order-book signal work, and the writing-up that makes any of it mean something to somebody else.

The research pieces on this site come from the same impulse pointed at the news instead of a chain. Something looks load-bearing, so I go pull on it, check the claims against each other, and draw what I find.

jaywurrly · Full-Stack Data Engineer · On-chain Analyst

Two illustrated sloths: one in a star-patterned wizard robe and orange beanie holding a staff, the other in a white and purple toga wearing a gold laurel wreath.
The wizard and the emperor. One reads the data, the other decides what to do about it.

Education

San Francisco, CA

MSc, Business Analytics

Golden Gate University · In progress — advanced Python, AI/ML, big data analytics

Sacramento, CA

BA, Psychology

California State University, Sacramento

Capabilities

On-chain

  • Solidity (Hardhat, OpenZeppelin)
  • Chainlink VRF & Automation
  • Chain indexers (persistent, not scraped)
  • wagmi / viem / ethers.js
  • Multi-chain — Avalanche, Ethereum, Base
  • Emission & money-flow reconstruction

Data engineering

  • MongoDB schema & index design
  • ETL pipelines
  • Aggregation pipelines at scale
  • Query optimization
  • Prisma / PostgreSQL
  • Real-time event tracking

Analysis & ML

  • Graph ML — node2vec, Louvain clustering
  • Order-book signal analysis
  • Time-series & backtesting
  • Jupyter / pandas / NumPy
  • SQL & Dune Analytics
  • Data visualization

Product

  • Next.js (App Router) & React
  • TypeScript
  • Vite
  • Tailwind CSS
  • Vercel deployment
  • Contract test suites

How this paper is made

  1. 01

    Every figure names its source and the date it was taken.

  2. 02

    Charts are drawn by hand from primary data: filings, chain records, archives.

  3. 03

    Corrections are recorded on the page rather than overwritten.