Statistician | PhD Candidate in Statistics (PPGMNE/UFPR) | Credit Risk & Fraud Analytics | Data Scientist @ Stix
- Data Science Specialist @ Stix, leading Advanced Analytics: ~30 ML models in production, fraud detection in point redemption, and dashboards for a 16M-member loyalty ecosystem
- PhD Candidate in Statistics (PPGMNE/UFPR, advisor Wagner Hugo Bonat), researching MCGLM-Graph — extending Multivariate Covariance GLMs with graphical-model representations of residual dependence (GGM & DAG layers)
- 10+ years in credit risk & fraud modeling across HSBC · Bradesco · ClearSale · Boa Vista SCPC
- Registered Statistician (CONFE)
Research interests: Graphical Models · Bayesian Networks · Multivariate GLMs · Computational Statistics · Credit Risk & Fraud Modeling
 Generalized Kumaraswamy regression for bounded (0,1) data 
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 Companion 7-family bounded distribution engine (C++/RcppArmadillo) 
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 Beta regression for interval-censored scale outcomes · with W. Bonat 
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 37 optimal binning algorithms & WoE for credit scoring 
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Also on GitHub: dscoder (AI code-generation agent for data science) · rnp (teaching toolkit behind the R na Prática book)
Credit Scoring PD/LGD/EAD Fraud & AML Bayesian Statistics GLM/GAM/GLMM MCMC Survival & Multivariate Analysis Causal Inference XGBoost/LightGBM
- Ph.D. in Statistics (in progress, PPGMNE/UFPR, 2024–2027) — Extensão de Modelos MCGLM: Uma Abordagem via Modelos Gráficos Probabilísticos (MCGLM-Graph) · advisor Wagner Hugo Bonat · pré-defesa concluída em 2026
- M.Sc. in Statistics (PPGMNE/UFPR, 2021–2023) — Beta regression models for scale data
- B.Sc. Statistics (UFPR, 2009–2013) · MBA Business Intelligence (Universidade Positivo, 2014–2015)
Open to collaborations on statistical modeling, credit risk, graphical models, and R package development.
personal_attributes <- list(
favorite_distribution = "(gkw) Generalized Kumaraswamy Distribution",
life_motto = "In God Trust",
superpower = "Finding patterns in chaos",
currently = "Turning residual covariance matrices into graphs")