Hello World

I'm Lucas Mendes, a Data Scientist focused on LLMs and AI-Driven Analytics.

About

Hi! I'm Lucas, a Data & AI specialist focused on extracting actionable insights from complex data. With 5+ years in LLMs, NLP, data engineering, and analytics, I leverage Python, SQL, and cloud platforms (AWS/GCP) to deliver scalable AI solutions. Currently pursuing a Postgraduate in Machine Learning Engineering, I explore advanced NLP and Explainable AI to drive business impact. My project, Music MoodAI, combines research and innovation to analyze emotions in music lyrics using AI.

View My CV

Expertise on

Data Scientist, AI Engineer, ML Engineer, Data Engineer, Data Analyst, and Lifelong Learner

Experience

Strategic analytics partner supporting product, operations, and growth teams by translating data into clear business insights. Drive KPI visibility and product performance analysis through SQL (BigQuery, Postgres), BI tools (Looker Studio, Metabase), and AI-powered automation with LLMs to accelerate decision-making, efficiency, and sustainable growth.

Focus: Product & operations analytics, AI-first automation, and data-driven decision support in a high-scale fintech environment.

Led AI initiatives for OCR, NER, and document classification using Generative AI tools (Gemini, Claude, ChatGPT), achieving 98% accuracy in automating legal workflows. Designed serverless AWS architectures (Lambda, SQS, SNS) and applied AWS Bedrock for document summarization and text generation, improving scalability and performance. Enforced Clean Code, SOLID, and CI/CD practices to ensure software quality. Collaborated with legal and business teams to align AI solutions with strategic goals.

Highlight: 1st place in an internal hackathon with a custom RAG solution for legal document retrieval.

Education

Postgraduate focused on Machine Learning Engineering, covering ML, DL, and MLOps with hands-on projects using AWS SageMaker, Docker, and CI/CD pipelines. Developed and deployed generative AI models (LLMs, GANs, BERT) and explored cloud-based data architectures for scalable AI solutions. Applied experiment tracking, monitoring, and model versioning best practices to ensure reliable production workflows.

Highlight: Second place in the Tech4Change hackathon with Darwin, an AI-driven employability ecosystem.

Bachelor’s degree with a strong foundation in data structures, algorithms, OOP, databases, and artificial intelligence. Conducted academic research applying AI and emotion recognition to Brazilian music, integrating NLP and deep learning techniques.

Highlight: Awarded 1st place at the 26th Scientific and Technological Initiation Symposium (FATEC-SP) and the 31st Scientific, Technological, and Innovation Forum (UNISAGRADO) for outstanding research in applied AI, focusing on recognizing emotions in song lyrics.