Data Science undergraduate at UNIR (Spain), currently working as AI QA Engineer Intern at ObviousFuture GmbH — a company specialising in secure, on-premise AI systems for enterprise clients across Europe.
I build end-to-end machine learning pipelines and validate AI systems with the same analytical rigour. My most recent project, CardioRisk ML, is a full cardiovascular risk prediction pipeline (10,000 patients · AUC 0.866 · Recall 0.863 at clinical threshold) — available in my Portfolio. I also bring hands-on experience in functional and regression testing of AI-powered products, defect tracking, and cross-functional collaboration with engineering teams.
My background in Sports Science research (UFSC, Brazil) built a strong foundation in statistical analysis and evidence-based decision-making — skills I now apply directly to Data Science and AI quality workflows.
🔍 Open to junior roles in Data Science, Machine Learning, or AI/ML QA · Europe · Remote-friendly
Languages
ML & Data Science
BI & Tools
🤖 AI QA Engineer Intern — ObviousFuture GmbH · 2026 – Present · Remote, Spain
Designing and executing 50+ functional, regression, and exploratory test cases for AI-powered enterprise software. Analysing model outputs to detect systematic failure patterns, tracking defects, and collaborating with data science teams to validate AI features prior to production deployment.
🏋️ Head Coach & Operations Coordinator — MoovBox · 2022 – 2024 · Brazil
Designed cardiometabolic programmes using heart rate and performance data; coordinated operations for a team of 6+ coaches; applied evidence-based methodologies to group fitness programming.
🏋️ CrossFit & Performance Coach — RedMob CrossFit · 2015 – 2021 · Brazil
Monitored and interpreted performance metrics for 20+ athletes per class; designed individualised training programmes using biometric data and statistical analysis.
📘 B.Sc. in Data Science (in progress) — Universidad Internacional de La Rioja (UNIR), Spain · 2025 – Present
📗 Data Science Professional Programme — Data Science Academy · 600+ hours · 2023 – 2025
Machine Learning · Big Data · NLP · Data Engineering · Power BI · Azure ML
📙 B.Sc. in Physical Education (Sports Science) — UFSC, Brazil · 2015 – 2020
Scientific research groups · statistical analysis · peer-reviewed publications
All projects are organised in the Portfolio repository.
| # | Project | Description | Key Result | Tech | Status |
|---|---|---|---|---|---|
| 01 | 🐾 Mexikans Analytics — Demand Forecasting | Operational demand forecasting for a veterinary clinic network. EDA, feature engineering and predictive modelling. | Business-oriented forecasting models | Python, Pandas, Scikit-learn | ✅ Complete |
| 02 | 🫀 CardioRisk ML — Cardiovascular Risk Prediction | End-to-end ML pipeline on 10,000 synthetic patients. 8 engineered clinical features, 6 algorithms, SMOTE, threshold optimisation. | AUC 0.866 · Recall 0.863 · +25.6% Precision vs baseline | Python, Scikit-learn, XGBoost, SMOTE | ✅ Complete |
🇧🇷 Portuguese — Native | 🇪🇸 Spanish — Fluent (C1) | 🇬🇧 English — Intermediate (B1, actively improving)
