Experience
I’ve been working with machine learning, data, and AI for the past 5 years, and I’m always motivated by building practical solutions to real problems. Whether it’s developing models, improving workflows, or experimenting with new ideas, I enjoy the process of creating tools that are both smart and useful.
Outside of work, I’m passionate about learning new things, whether it’s through reading, exploring new technologies, or diving into a great video game. I also love to travel and find a lot of inspiration in experiencing different cultures and perspectives.
This portfolio is a collection of projects I’ve built, experiments I’ve explored, and lessons I’ve picked up along the way. I’m always open to connecting, learning from others, and building something great together.
If you’re working on something interesting, want to collaborate, or just have a question — don’t hesitate to reach out.
What People Say About My Work
"The Best student I've ever had."
"Best computer guy in the world."
"Pedro is an exceptional developer who delivered beyond our expectations."
Data Scientist
Description:
Leading AI-driven initiatives to enhance pricing strategies and optimize customer selection for international telecom partnerships.
Key Responsibilities:
- Developed a dynamic pricing model using deep learning on unbalanced datasets
- Designed a comprehensive quality scoring system that integrates survey data, partner costs, and commercial agreements to recommend optimal international roaming partners
- Collaborated on Retrieval Augmented Generation (RAG) projects, contributing optimized pipeline strategies to accelerate solution delivery across teams.
Software/Prompt Engineer
Description:
Led the development of AI-powered tools and a RAG-based ETL pipeline to streamline company information retrieval for a venture capital firm.
Key Responsibilities:
- Engineered advanced ETL pipelines transforming SQL data into embeddings, reducing processing time by 72x
- Developed a hybrid RAG-powered recommendation system combining vector search and NoSQL queries for tailored content delivery.
- Built a sentiment analysis pipeline with granular insights for product and company-level analysis, enhancing interpretation.
- Created an LLM-based tool for summarizing web content and email communications, streamlining content review processes.
Intern in Data Science
Description:
Contributed to data-driven decision-making through dashboard development, performance optimization, and training initiatives.
Key Responsibilities:
- Designed and maintained interactive Power BI dashboards to support business intelligence efforts.
- Improved data handling performance by implementing materialized views for large-scale tables.
- Led team training sessions and created documentation to streamline Power BI adoption and improve productivity.
Machine Learning Research Intern
Description:
Contributed to research and development of deep learning and classical ML solutions for document processing, CV, and NLP tasks.
Key Responsibilities:
- Implemented UNet-based models for pixel-wise semantic segmentation for improving document scanning.
- Developed Named Entity Recognition (NER) models for automatic file naming in document scanning applications.
- Created classifiers for automatic document categorization
- Conducted classical machine learning workshops to share foundational ML knowledge and practical skills with co-workers.