8000 Nachoxt17 (Ignacio Ceaglio) · GitHub
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I don't believe in luck, I believe in statistics.
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I don't believe in luck, I believe in statistics.
59 followers · 21 following

Achievements

Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: QuickdrawAchievement: StarstruckAchievement: Pull Shark

Achievements

Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: QuickdrawAchievement: StarstruckAchievement: Pull Shark

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Nachoxt17/README.md

👨‍💻 Ignacio Ceaglio 💻🚀

Data Scientist and Machine Learning Engineer-Scientist Python | Data Engineer SQL.
Senior Solidity Developer + Technical Project Architect + People's Person = Blockchain C.T.O. On-Demand

👨🏻‍💻My professional passion is in planning, architecting, developing and testing Machine Learning Models that help to research Valuable Investment and Business opportunities for the shareholders, and in talking/networking with clients and company partners. I have a background in Full-Stack JavaScript Web Development at the beginning of my career, and later I developed a strong background in Solidity Smart Contracts Development; but since then I have specialized in Data Science and Machine Learning Engineering in Python.

My clients and co-workers (Recommendations below) have praised me for being, in their own words; “very curious, pro-active, positive, humble, helpful, diligent, intelligent, passionate and ambitious”.👨🏻‍💻

📜 Creator of the ERC-7776: Transparent Financial Statements Standard.
🔭 Artizen.Fund Web2.0-to-Web3.0 Transition Architect.
⛓ Open Art Market (Production) Foundational Solidity Smart Contracts Developer.
📊 AngelBlock Early Investor.
🌦 ANZAIRU and ⚽️VERTULO ex-C.T.O.

followers total stars profile views linkedin upwork

🛠️ Languages and Tools

Solidity

JavaScript

TypeScript

Hardhat

Python

HTML

CSS

React

Redux

NodeJS

mongodb

GitHub

Git




🗳️ What people say:

Reviews in Linkedin

🏆 GitHub Trophies:

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  1. Retail-Business-Data-Analytics Retail-Business-Data-Analytics Public

    Conducted exploratory data analysis on multi-store sales datasets, uncovering patterns and delivering actionable insights in seasonal trends, customer behavior, and product performance.

    Jupyter Notebook 1

  2. Industrial-Machinery-Predictive-Maintenance-M.L.-Model Industrial-Machinery-Predictive-Maintenance-M.L.-Model Public

    Built a machine learning model to predict machinery failures using historical time series sensor data. Applied feature engineering, model tuning, and scikit-learn pipelines to improve prediction ac…

    Jupyter Notebook 1

  3. Loan-Repayment-Financial-Analysis Loan-Repayment-Financial-Analysis Public

    Analyzed borrower data to identify key financial correlations impacting loan repayment success; delivering clear, data-driven risk insights.

    Jupyter Notebook 1

  4. Data-Warehouse-SQL-End-to-End-E.T.L. Data-Warehouse-SQL-End-to-End-E.T.L. Public

    Designed and implemented a complete Data Warehouse solution, defining data architecture, designing multi-layer (Bronze, Silver, Gold) E.T.L. pipelines, and building star schema models in SQL script…

    TSQL 1

  5. Real-Estate-Price-Estimator-for-Tokyo Real-Estate-Price-Estimator-for-Tokyo Public

    Machine Learning model to estimate Tokyo real estate prices, using E.D.A. and Linear Regression techniques on housing datasets to predict market values with improved precision.

    Jupyter Notebook 1

  6. Apache-Spark-Processing-with-A.W.S.-E.M.R. Apache-Spark-Processing-with-A.W.S.-E.M.R. Public

    This project demonstrates the use of Amazon Elastic Map Reduce (EMR) for processing large datasets using Apache Spark. It includes a Spark script for ETL (Extract, Transform, Load) operations, AWS …

    Python 1

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