Career-changer with a unique background in culinary arts bringing precision, creativity, and problem-solving skills to the world of data science. Recently graduated from 4Geeks Academy's Data Science program, where I built production-ready ML solutions and mastered the full data science pipeline.

What drives me: Turning complex data into actionable insights and building intelligent systems that solve real-world problems.

Currently: Actively seeking Data Analyst/Data Scientist opportunities to apply my skills and continue growing in the field.

iago = {
    "role": ["Data Scientist", "ML Engineer", "Python Developer"],
    "currently_learning": ["Advanced ML", "MLOps", "Deep Learning"],
    "interests": ["Predictive Analytics", "Model Explainability", "Production ML"],
    "looking_for": "Data Analyst/Data Scientist opportunities"
}

Advanced Financial Machine Learning System for Market Regime Detection & Signal Enhancement

• 🧠 Combines Hidden Markov Models (HMM) with meta-labeling to improve trading signal quality
• 📊 Integrates market data, macroeconomic indicators, and historical economic events
• 🏗️ End-to-end pipeline: data extraction → preprocessing → modeling → visualization
• 💾 SQLite-based data persistence for reproducibility and efficient analysis
• 🖥️ Interactive Streamlit dashboard inspired by Bloomberg Terminal interfaces
• ⚙️ Leverages advanced tools: TA-Lib, XGBoost, HMMlearn

🚀 Tech: Python, Pandas, NumPy, HMMlearn, XGBoost, TA-Lib, Streamlit, SQLite

Autonomous Multi-Agent AI System for Financial News Processing & Audiovisual Generation

• 🤖 Multi-Agent Editorial Team: Coordinates local LLMs (Qwen2.5 & Gemma) to scrape, filter, and write high-quality financial scripts.
• 🎙️ Neural Voice & Audio Post: Converts text to speech via Kokoro ONNX and processes audio with FFmpeg (parametric EQ and EBU R128 normalization).
• 🎨 Dynamic Video Composition: Animates a pixel-art presenter by mapping mouth states directly to audio RMS levels.
• 🌐 Automated Resource Scraping: Uses Selenium and undetected-chromedriver to gather and validate contextual visual assets.
• 📊 Structured Ingestion: Utilizes Pydantic for robust structured data flow throughout the pipeline.

🚀 Tech: Python, Ollama, Pydantic, Kokoro, FFmpeg, Selenium, OpenCV, PIL, newspaper3k

End-to-End ML System for Credit Risk Assessment

• 📊 Built complete pipeline: data cleaning → feature engineering → model training → deployment
• 🤖 Trained and compared multiple ML models achieving AUC: 0.81
• 💡 Implemented SHAP for model explainability and transparent decision-making
• 🚀 Deployed production-ready API with FastAPI

🚀 Tech: Python, Scikit-learn, SHAP, FastAPI, Pandas

• 🤖 Advanced Multi-Agents Locally: Ollama, LangGraph, and Agentic RAG architectures.
• ☁️ MLOps & GenAIOps: Containerization (Docker), model tracking, and efficient deployment of local/open-source LLMs.
• ⚡ Performance Optimization: Quantization, ONNX runtime, and hardware acceleration for AI workloads.

Seeking opportunities as a Data Analyst or Data Scientist where I can leverage my analytical mindset, technical skills, and unique problem-solving approach to deliver data-driven solutions that create real business impact.

What I bring to the table:

• 🔍 Strong analytical thinking & attention to detail
• 💡 Creative problem-solving from diverse background
• 🛠️ Hands-on experience with end-to-end ML pipelines
• 📚 Fast learner committed to continuous improvement
• 🤝 Team player

I'm actively looking for Data Analyst/Data Scientist opportunities and open to collaborations!