# Luciano Lazarte

> Full Stack Developer. React, TypeScript, NestJS, GraphQL. Fintech product at Poncho Capital. Salta, Argentina. Open to full-remote roles.

I design and build fintech products people can actually use.

Full Stack Developer. Building a retail investing product so people with no prior finance experience can invest. React and TypeScript on the frontend, NestJS and GraphQL on the backend.

- Location: Salta, Argentina
- Email: lazarteluciano23@gmail.com
- GitHub: https://github.com/Jehp23
- LinkedIn: https://www.linkedin.com/in/lucianolazarte23
- Company: [Poncho Capital](https://ponchocapital.com)

## Selected work

### Poncho Capital · Retail Investing

An investing product for people with no prior finance experience. I ship the stack end to end in a small team: React and TypeScript on the frontend, NestJS and GraphQL on the backend. Web flows in production.

Stack: React, TypeScript, NestJS, GraphQL. Links: [Site](https://ponchocapital.com).

### EstacionaSalta · Measured parking

Measured-parking product for the city of Salta. First place at Puna Tech 2026, City Track.

Stack: TypeScript, React, Next.js. Links: [Demo](https://estacionasalta.vercel.app), [Video](https://www.youtube.com/watch?v=ThcJASSvIPU).

### INK · Smart Contract Risk Intelligence

Smart-contract risk analyzer. Paste an address and get a deterministic 0–100 score plus a plain-language explanation.

Stack: Next.js, TypeScript, Avalanche. Links: [Demo](https://ink-three-iota.vercel.app), [GitHub](https://github.com/Jehp23/ink-risk-intelligence).

### Cello · Institutional payments

Private institutional payments using eERC20 on Avalanche.

Stack: TypeScript, Avalanche, eERC20. Links: [Demo](https://cello-avax.vercel.app).

### QuantLab · Quant Research Platform

Quant research platform: VaR, Monte Carlo, efficient frontier, and BYMA options.

Stack: FastAPI, Python, Next.js, TypeScript. Links: [Demo](https://quantlab2.vercel.app), [Backend](https://github.com/Jehp23/quantlab-back), [Frontend](https://github.com/Jehp23/quantlab-front).

### Credit Risk · ML Ensemble

Loan default prediction: EDA, SMOTE, PCA, and an ensemble of XGBoost, Random Forest, Gradient Boosting, and a Voting Classifier. AUC 0.942.

Stack: Python, XGBoost, scikit-learn, SMOTE. Links: [GitHub](https://github.com/Jehp23/riesgo-crediticio).

## Where to look next

- [About Luciano Lazarte](https://lucianolazarte.vercel.app/about)
- [Contact](https://lucianolazarte.vercel.app/contact)
- [Privacy](https://lucianolazarte.vercel.app/privacy)
- [Luciano Lazarte developer resources](https://lucianolazarte.vercel.app/developers)
- [llms.txt](https://lucianolazarte.vercel.app/llms.txt)
- [Sitemap](https://lucianolazarte.vercel.app/sitemap.xml)
- [OpenAPI](https://lucianolazarte.vercel.app/openapi.json)
- [MCP handshake](https://lucianolazarte.vercel.app/.well-known/mcp)