Welcome! Bonjour!

Hi, I am Rafael, Data Scientist based in Toronto 🇨🇦

Socials are found below

Hey there! 👋 I’m Rafael, a data scientist with a deep passion for harnessing the power of AI and ML to uncover game-changing insights and build cutting-edge solutions. With 8+ years of experience in analytics, I’ve spent the last 4 years diving deep into Natural Language Processing (NLP), Large Language Models (LLMs), and Responsible AI, focusing on Explainable AI, Model Fairness, and Differential Privacy.

Throughout my career, I’ve tackled complex data challenges across highly regulated industries such as banking, finance, and utilities. By combining my technical expertise in machine learning, deep learning, and data mining with strategic planning and stakeholder collaboration, I’ve successfully executed impactful AI projects that drive organizational success.

🦸‍♂️ Technical Expertise

  • Machine Learning: Supervised learning, unsupervised learning, reinforcement learning, ensemble methods, and model optimization
  • Deep Learning: CNNs, RNNs, LSTMs, Transformers, and attention mechanisms
  • NLP and Generative AI: Large Language Models, Text preprocessing, feature extraction, sentiment analysis, topic modeling, named entity recognition, and text generation
  • Data Mining: Pattern recognition, anomaly detection, clustering, and association rule mining
  • Programming Languages: Python, R, SQL, and Scala
  • Libraries and Frameworks: TensorFlow, PyTorch, Scikit-learn, NLTK, SpaCy, and Pandas

🌟 Experience Highlights

  • Championed Responsible AI practices by integrating fairness testing in model development, conducting 30+ pre-deployment model audits focusing on bias and fairness, and data privacy as part of the model governance process
  • Co-established a R&D group in GCash to explore new use cases in the organization
  • Co-developed LLM Operations Framework with MLOps and MLE teams
  • Implemented Retrieval Augmented Generation (RAG) and Text-to-SQL agents using Azure OpenAI GPT-4o and Cohere Rerank model
  • Collaborated on pioneering GCash’s first AI Ethics charter and roadmap while training 100 data practitioners on model limitations, consequences, and transparency, significantly advancing Responsible AI practices organization-wide

🔬 Project Interest/s

  • Generative AI and Natural Language Processing (NLP) particularly LLM applications and Multi-agents
  • Model Fairness and Privacy Engineering
  • Recommender Systems and Graph Analytics
  • Geospatial Machine Learning

đź“š Sample Work

Some of my projects are found under Projects. (I’m trying to produce write-ups for all of them)