Ayrton Bruno

At Musa, I build Python data pipelines and AWS infrastructure that make data available for analyses, dashboards, and internal products. I also use Generative AI to extract and structure unstructured legal data, reducing manual work for the legal team by 95%.

Previously at Saúde Bliss, I used exploratory analysis, statistical testing, A/B tests, regression models, and AI text classification to improve product decisions. My work helped reduce support tickets by 50%, cut pending-issue resolution lead time by 20%, and increase product adoption from 12% to 26%.

I enjoy turning ambiguous product and operational questions into measurable hypotheses, analyses, and practical improvements. I work closely with stakeholders to diagnose root causes and identify opportunities in internal systems and products.

With a quantitative foundation from Materials and Manufacturing Engineering at USP, I'm seeking Data Scientist opportunities focused on advanced analysis, predictive modeling, and business impact.