Renato Rangel

• Designed and deployed a resume–job description matching tool using LangChain, OpenAI embeddings, and Pinecone, helping clients identify top candidates 30% faster.
• Built a chatbot assistant powered by AWS Bedrock and LangChain that explains candidate–job fit in natural language, improving recruiter decision confidence and reducing manual screening effort.
• Automated document ingestion, chunking, and metadata extraction with Python and FastAPI, enhancing vector search precision and increasing shortlist accuracy by 25%.

• Designed, trained, and deployed machine learning models on AWS infrastructure to deliver real-time personalized decision support, enabling users to select optimal medical plans based on contextual data analysis. This work contributed to creating a patent.
• Designed and implemented workflows integrating large language models (LLMs) to enhance natural language understanding and automate data extraction of medical documents, and collaborated with engineering teams to scale these solutions for production deployment.

Led data science initiatives for a Brazilian healthcare platform, driving the development of innovative solutions and the company’s data strategy.

• Conducted comprehensive churn analysis, leveraging behavioral data to identify at-risk customers and recommend actionable retention strategies.
• Collaborated with cross-functional teams to align data-driven insights with business objectives, optimizing healthcare outcomes and operational efficiency.
• Established a scalable data infrastructure, enabling the integration and analysis of behavioral and clinical datasets.