Skills

Python, SQL, data visualization, BI tools, analytics, objective measurement, statistical analysis, machine learning, experimentation, causal inference, NLP, LLMs, PyTorch, Keras, TensorFlow, Kubernetes, Docker, container-based deployments, R, Java.

About

Aurélio Moraes is a data scientist and machine learning expert who currently works at Visian Systems. He graduated with a degree in Computer Engineering from the Pontifical Catholic University of Rio de Janeiro in 2004 and later earned his Master's degree in Informatics from the same university in 2007. In 2015, he completed his PhD in Informatics from PUC-Rio, where he focused on mapping seismic events using data clustering algorithms. He's currently teaching Machine Learning at Volta Redonda University in Rio de Janeiro / Brazil.

With a solid background in computer science, Aurélio has specialized in graphics processing and machine learning algorithms and has applied his expertise in several projects in the oil and gas industry, particularly in computer vision. He has also developed expertise in data analysis, including data mining and predictive modelling, and is skilled in programming languages such as Python, R, and Java.

Throughout his career, Aurélio has demonstrated a strong ability to work collaboratively and communicate complex technical concepts to both technical and non-technical audiences. He is a highly analytical thinker with a creative approach to problem-solving and is always looking for innovative ways to apply his skills to real-world challenges.

Aurélio builds and deploys advanced machine learning models and designs robust analytics engines for high-end digital products. Concurrently, he takes the initiative to develop and promote knowledge sharing and code reuse, fostering a collaborative environment. Collaborating closely with other data scientists, he/she solves complex issues pertinent to data ingestion, curation, modality integration, model performance, and generalization. 

Furthermore, Aurélio is adept at effectively communicating the analytics approach to business partners, catering to technical and non-technical audiences. Being a staunch advocate for data-driven decision-making, he focuses on educating peers and clients on the nuances of solving problems, emphasizing the "how and why" behind each strategy. Leading analytic approaches, he integrates work into applications and tools seamlessly, working hand in hand with data engineers, business leads, analysts, and developers, thus contributing to a holistic and efficient problem-solving environment.