• Cut incident triage latency by 5 to 10 minutes per ticket for the Customer Support team, preventing SLA-driven financial losses with enterprise clients, by automating (n8n) the incident routing pipeline to ingest OTRS tickets, extract relevant client context, trigger real-time Discord alerts to stakeholders, and auto-generate fully detailed Kanban cards for immediate developer action.
• Saved 3 hours per week in manual audits and prevented escalation delays by engineering a proactive governance bot (n8n) that automatically flags customer requests unanswered for 7 or more days.
• Improved planning under uncertainty across business units by replacing subjective deadline-risk discussions with probabilistic completion scenarios, through a Monte Carlo forecasting engine with automated data ingestion and standardized management reporting.

Aprix is a SaaS company providing AI-driven pricing solutions for major industries in Latin America. Our technology helps large-scale businesses optimize pricing strategies and operational efficiency through scalable data products.

• Led end-to-end research and proof-of-concept in Amazon EU Supply Chain (middle-mile) to improve short-term labor planning guardrails for Sort Centers over 24-hour and 48-hour horizons.
• Designed and validated predictive approaches under temporal dependencies, censored outcomes, class imbalance, and site-specific behavior using SQL-based data extraction and Python feature engineering.
• Built and evaluated ML pipelines in AWS SageMaker Studio against operational heuristics and observed a 27.4% uplift over baseline for same-day forecasting across 10 UK Sort Centers.
• Partnered with BI, Science, and Operations stakeholders through recurring technical and business reviews to translate model behavior into production-readiness trade-offs.

• Awarded a research scholarship from Brazil's National Council for Scientific and Technological Development (CNPq), supported by BIOS (Brazilian Institute of Data Science).
• Conducted research on interpreting machine learning predictions for diagnosing SARS-CoV-2 from symptoms, using SHAP and LIME methods.
• Link to the project

• Eliminated software crashes during large-dataset imports by engineering token-based batch processing of 50,000 rows per chunk, integrating SQL connections with C++ simulation logic.
• Conducted an analysis of no-code machine learning frameworks, identified RapidMiner as the best viable option due to usability and feature set, and upskilled the engineering team with a case study on steel-industry energy consumption prediction using Random Forest classifiers.

FlexSim Brasil is a highly specialized tech consultancy leveraging advanced Digital Twin and 3D simulation platforms to optimize complex, large-scale industrial and logistics operations.

• Optimized analysts' time and resources by 27% and improved battery fault-detection precision to 73% by replacing legacy rule-based heuristics with an end-to-end ML approach in a Motorola-funded R&D project.
• Leveraged interpretable ML techniques (SHAP) to uncover hidden diagnostic patterns and expand expert manual criteria with data-driven insights.

Instituto de Pesquisas Eldorado is one of Latin America's premier R&D institutes (1,600+ engineers), partnering with global tech leaders such as Motorola to develop software, AI, and Industry 4.0 solutions.

State University of Campinas - UNICAMP

Bachelor's degree, Industrial Engineering - March 2020 - December 2026

• UNICAMP is one of Brazil's leading public research universities and a major center for science and innovation. In the QS Latin America and Caribbean 2026 ranking, UNICAMP is 3rd in Latin America.
• Activities and societies: Physics Instructor at Cursinho Pre-Vestibular Colmeia (6h/week) and Teaching Assistant (300+ hours in Calculus I, Linear Algebra, Analytic Geometry, and General Physics I).
• Relevant coursework: Algorithms and Computer Programming, Statistics and Probability, Numerical Methods, Operations Research I and II, Multicriteria Decision Support Methods, Machine Learning, Systems Simulation, Economic Engineering, Quality Engineering, and Project Management.