Building robust systems to turn data into insights and help decision making.
I’m a Data Scientist and Data Engineer focused on build end‑to‑end machine learning systems that combine data engineering, statistical modeling, and cloud‑native architectures. I began my career in 2019, creating automation solutions with VBA and writing PL/SQL queries. In 2020, I transitioned fully into the Analytics field, working on data projects that blended 80% data science and 20% data engineering, which shaped my hybrid technical profile. From 2020 to 2023, I worked in the energy distribution sector, developing solutions aimed at cost reduction and operational efficiency, including:
- optimization of operational base allocation
- maintenance performance indicators for power distribution networks
- meter failure prediction models
- automated pipelines for logistics indicators
- outage forecasting for distribution networks After 2023, I moved into consulting to work with cloud‑native applications, collaborate with diverse teams, and gain exposure to projects across multiple industries. Since 2024, I’ve been part of an international, global team, designing and deploying machine learning applications on AWS with a focus on sales‑driven solutions.
-
🤖 ML Systems
- Statistics
- Machine-learning (classic)
- NLP and first steps into LLMs
-
🧱 Data Engineering
- ETL / ELT pipelines
- Data modeling and analytics engineering
- Event-driven
-
☁️ Cloud-Native & Scalable Architectures
- Containerized services
- Orchestrated workflows
- Serverless applications (focus)
-
🎓 Education & Mentorship
- New achievements/implementations inside company (knowledge sharing)
- Mentoring interns on my last jobs in Brazil
- Modelling and Training · ML Pipelines
- Deploy and MLOps with SageMaker
- Neural Networks · Deep Learning · TensorFlow
- Feature Engineering · scikit‑learn
- ETL / ELT Pipelines
- Data Modeling & Analytics Engineering
- Batch Data Processing
- Containerized Microservices
- Cloud-Native AI Systems
- CI/CD & Production Deployments