At Farmers Insurance, I develop statistical and machine learning models for auto insurance loss modeling. I analyze insurance data to identify loss drivers and risk patterns for claim frequency and severity.
At Nestlé, I delivered over R$500K in business value through data transformation and automation pipelines. I also built an S-curve model to identify a selling price that maximizes revenue without reducing sales.
At Vale S.A., I built a model that detected about 60% of high-emission events, triggering automated fog cannons for dust suppression. I created CI/CD pipelines for continuous model retraining and deployment, and delivered a solution scalable to 43 mining/courtyards units.
At Trademaster, I developed credit risk models that achieved 85% accuracy in default prediction and reduced exposure by about R$2M. I’m pursuing a Master's degree in Computer Science at UFJF, with thesis proposals in time series forecasting and anomaly detection.
