GILSON MACHADO

Data Scientist

https://talent.gravityer.com/gilson-machado

Brasil

Key Strengths

Demonstrated proficiency in various data science methodologies including Bayesian statistics, machine learning (XGBoost, LSTM, Q-Learning), and statistical analysis.
Strong practical experience with Jupyter Notebook for data analysis and model development.
Projects show a good understanding of model evaluation, validation, and fairness analysis (e.g., LOO comparison, TIF/SEM, PPC validation, Yen's Q3, SHAP, Equalized Odds violation).
Experience with both frequentist and Bayesian A/B testing, indicating a comprehensive understanding of experimental design.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic in nature, focusing on diverse data science topics. While this demonstrates intellectual curiosity and a broad skill set, there is no information on collaborative projects or professional experience, making it difficult to assess cultural fit within a team or corporate environment. The projects align well with a Data Scientist role, but the lack of professional context limits a full cultural fit assessment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest an analytical and problem-solving mindset.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

tri-irt-bayesian

June 15, 2026 – Present

Bayesian IRT — Rasch (1PL) vs 2PL with PyMC | LOO comparison, TIF/SEM, PPC validation, Yen's Q3 diagnostic

View Project

analise-acidentes-prf-para

June 12, 2026 – Present

Análise de segurança viária — PRF/DATATRAN Pará 2024–2025 | Regressão Ordinal, GLMM, XGBoost + SHAP, Predição de Risco 2026

View Project

iterated-prisoners-dilemma-marl

June 12, 2026 – Present

Multi-agent Q-Learning in the Iterated Prisoner's Dilemma — cooperation emergence, 5 factorial experiments, statistical analysis

View Project

tesla-lstm-forecast

June 12, 2026 – Present

Tesla stock prediction with LSTM — MAPE 4.94%, 30-day forecast, zero data leakage

View Project

compas-fairness-analysis

June 12, 2026 – Present

Racial bias in COMPAS algorithm — Equalized Odds violation, FPR 2x higher for Black defendants

View Project

ab-testing-frequentist

June 12, 2026 – Present

Frequentist A/B testing — t-test, Shapiro-Wilk, Cohen's d, conversion rate, ROI, CPC

View Project

bayesian-ab-marketing

June 12, 2026 – Present

Bayesian A/B testing — ROPE, Bayes Factor, adaptive stopping. P(ad>psa)=100%, 97.4% data economy

View Project

Gilsonmm6

September 16, 2024 – Present

Gilsonmm6 — GitHub repository

View Project

Key Strengths

Demonstrated proficiency in various data science methodologies including Bayesian statistics, machine learning (XGBoost, LSTM, Q-Learning), and statistical analysis.
Strong practical experience with Jupyter Notebook for data analysis and model development.
Projects show a good understanding of model evaluation, validation, and fairness analysis (e.g., LOO comparison, TIF/SEM, PPC validation, Yen's Q3, SHAP, Equalized Odds violation).
Experience with both frequentist and Bayesian A/B testing, indicating a comprehensive understanding of experimental design.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest an analytical and problem-solving mindset.

GILSON MACHADO

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit