Anderson Neisse is a Statistics Manager with eight years of experience translating complex data into strategic decisions for public institutions, currently leading the Data Science and Statistics team at the Tribunal de Justiça de Mato Grosso. He holds a Master’s in Applied Statistics and Biometry and combines advanced ML/AI, CRISP-DM, and classical techniques like DEA to design data products that improve operational efficiency and benchmarking. His work includes an end-to-end clustering pipeline that reframed judiciary performance from volume to case complexity and a comparative analytics program that informs state-level policy and ranking strategy. Comfortable across Python, R, SQL and cloud environments, he bridges technical analysis and executive decision-making through actionable BI and storytelling. Unexpectedly, his background spans both public-sector jurimetrics and private-sector operational automation, giving him a rare mix of regulatory insight and hands-on process optimization.
8 years of coding experience
2 years of employment as a software developer
Master's degree Statistics, Master's degree Statistics at Universidade Federal de Viçosa
Bachelor's degree Statistics, Bachelor's degree Statistics at UFMT - Universidade Federal de Mato Grosso
Contributions:6 commits, 5 pushes, 1 branch in 1 year 1 month
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