Summary
Henrique Laureano is a Lead AI Engineer with 11 years of experience building production-grade AI and statistical systems for finance, risk, fraud, and operational value creation across enterprise environments. He blends deep-stats expertise (GLMs/GAMMs, survival, spatiotemporal models, Bayesian inference) with modern ML/LLM engineering (PyTorch/JAX, LangChain, Vertex AI, SageMaker, Databricks) to deliver end-to-end solutions—from probabilistic modeling to agentic RAG and DNN deployment. At Volvo and EBANX he led initiatives that translated advanced models into measurable business impact, including savings and forecasting accuracy gains and the delivery of “Zenith,” an agentic finance assistant integrated with BigQuery and Gemini. Comfortable in cloud, on-prem, and hybrid stacks, he also brings domain-honed judgment from clinical and epidemiological research to high-stakes financial applications. Not obvious at first glance: his academic work on high-dimensional spatial Bayesian models and competing-risks GLMMs underpins much of his practical ability to model complex dependencies in multivariate time-series and risk settings.
10 years of coding experience
2 years of employment as a software developer
PhD (not completed), Statistics, PhD (not completed), Statistics at KAUST (King Abdullah University of Science and Technology)
MSc (not completed), Statistics, MSc (not completed), Statistics at Universidade Estadual de Campinas
MSc, Statistics and Numerical Methods in Engineering, MSc, Statistics and Numerical Methods in Engineering at Universidade Federal do Paraná
Portuguese, English