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Miguel Cerne
Miguel Cerne
Software Engineer
// core

I build data systems for finance — the kind where being wrong is expensive.

Software engineer working where software, data, and quantitative finance meet. Currently at JGP, on the infrastructure behind financial-markets data.

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// what i do

Three disciplines, one thesis: use data to solve finance problems, and engineer the systems that make the solution dependable.

01
Software Engineering

Typed, tested systems — APIs, services, and the infrastructure that keeps them dependable in production.

02
Data Engineering

Pipelines and models built on data that spans years, with validation that catches leakage before production does.

03
Quantitative Finance

Financial-markets domain knowledge — the market structure and instruments the data and systems actually serve.

// rings

Selected work

data · finance

NeuraTrade

Unsupervised anomaly detection over 14 years of B3 equities with an LSTM-autoencoder, built so the methodology actually holds up.

key decision

Every decision is a logged ADR (18 of them, including ideas rejected with proof — Transformers, Optuna, weight decay), guarded by 32 tests and walk-forward validation against temporal leakage.

View project →Code ↗
system design

Toró D'Extoques

"Do you know what's in your own stockroom?" AI inside the registration flow a company already has: in four days we sanitized a 23,554-item industrial materials base — 57% of it got at least one proposal, 16,721 in total, including 1,124 merges and 6,083 NCM fixes — and a chat agent over MCP registers new items to the PDM standard.

key decision

The AI proposes, the rule confirms, a person approves. Merging two different items costs more than missing a duplicate, so one shared domain engine decides identity for the batch, the chat and the approval transaction; a similarity score only ranks; and every change is a proposal applied by the API in one transaction with audit, idempotency and version checks.

View project →Code ↗
system design

Olha o Pesado

An autonomous-robot MVP built on a clean observer-pattern core, so vision, control, and results stay decoupled.

key decision

Signals are typed — Frame, Control, Result — so each subsystem reacts to events without knowing about the others. Architecture as the feature.

View project →Code ↗
// more work
B3 Investimentos

A queryable terminal for 1,103 B3 stocks, REITs (FIIs) and ETFs — CVM and Yahoo data in SQLite, a Swagger-documented API, an MCP server for AI, screeners, live indicator views and Markowitz optimization down to whole shares.

Live ↗Code ↗
SnippetVault

A deployed full-stack vault for code and prompt snippets — JWT auth, tagging, search, favorites.

Live ↗Code ↗
Graph Theory Library

A personal library of graph representations and algorithms, built from the ground up.

Code ↗
Explorador Evolutivo

A browsable catalog of undergrad-thesis (TCC) ideas — filterable cards, a detail panel per idea, and two audience-scoped views over the same dataset.

Live ↗Code ↗
dotfiles

Fully customized environment, optimized for my end usages and colorschemes. Used tools: tmux, zsh, ghostty, neovim.

Code ↗
Cerne Neovim

A neovim distro fully-built on my specific needs and preferences.

Code ↗
// currently

Software Engineering Intern at JGP Crédito — building infrastructure for financial-markets data.

TypeScriptPythonNode/NestJSReactPostgreSQLDocker
// get in touch

Building something where data, finance, and reliability matter? Let's talk.

Message me on LinkedInGitHubmiguelcerne.dev@gmail.com
Miguel Cerne — Software engineer for data & finance systems