Estevan A.Machine Learning/AI Engineer
Skills
Currently engaged in master's studies and research on physics-informed neural networks (PINN) for petroleum reservoirs, integrating Partial Derivative Equation (PDE) models into deep learning applications.
Academic qualifications include a bachelor's degree in physics and a master's degree in artificial intelligence at PUC Rio within the electrical engineering department. Competencies encompass various Data Science frameworks, AWS Cloud Practitioner certification, extensive experience in Python (4.5 years), SQL, and expertise in machine learning and deep learning.
Career credentials demonstrate a diverse range of roles. Engagements include participation in a focused AI and data program at a Brazilian research center, contributions to digital transformation initiatives at an insurance company through analytics, data science, and AI, and involvement with a GovTech innovation laboratory. Additionally, experience as a Junior Researcher encompassed data analysis, scraping, and visualization tasks at the Federal University of Rio de Janeiro.
Programming experience totals four years with a focus on Python within data science and analytics, and two years in object-oriented structures. Comprehensive learning through distance platforms amounts to approximately 300 hours dedicated to machine learning and deep learning courses. Near completion is a 360-hour specialization in Machine Learning and Artificial Intelligence along with a scientific project at PUC Minas.
Proficiency in developing data science and artificial intelligence solutions is supported by the utilization of frameworks including Pandas, Numpy, Scipy, Sklearn, TensorFlow, Git, Dask, PowerBi, Matplotlib, Plotly, Seaborn, AWS, Azure, NLTK, StreamLit, Selenium, SQL, NoSQL, among others.
Research Assistant
8/1/2023 - Present
Conducted advanced research in the laboratory focused on Oil and Gas challenges. Specialized in the application of Physics Informed Neural Networks (PINN) to reservoirs, integrating deep learning with partial differential equations (PDEs) that govern the system. Developed proficiency in formulating and solving PDEs using PINN techniques, demonstrating the potential to apply these methods across various systems governed by PDEs.R&D Learner
12/1/2022 - 3/1/2023
Participated in a trainee program focused on AI at a prominent research center in Brazil. Developed expertise in exploratory data analysis and the design and development of state-of-the-art AI models. Contributed to backend development using AWS microservices, utilizing tools such as AWS Lambda, DynamoDB, and API Gateway. Conducted thorough AI literature reviews to stay abreast of industry advancements. Engaged in C# development for industrial applications. Gained proficiency with key tools and frameworks, including Sklearn, Keras, Pandas, Scipy, and Python, enhancing technical expertise in both AI and backend development environments.Data Scientist
8/1/2022 - 12/1/2022
Developed solutions for the AI and Engineering team focused on the insurance sector. Conducted big data exploratory analysis using Dask clusters and executed ETL (Extraction, Load, and Transformation) processes for non-structured data. Created insightful dashboards through PowerBI and developed robust pipelines to ensure smooth data flow. Engaged in thorough reviews of insurance AI literature. Acquired technical proficiency in Python, AWS, SQL, Pandas, Dask, Plotly, PowerBI, Git, and Numpy.Data Science Intern
1/1/2022 - 8/1/2022
Developed and maintained a machine learning pipeline leveraging Azure Form Recognizer. Conducted extensive exploratory data analysis utilizing Python to glean insights and inform decision-making processes. Performed SQL data analysis to create comprehensive reports and facilitate dashboard ingestion, ensuring data accuracy and accessibility. Crafted and optimized SQL Server procedures to streamline operations. Addressed complex technical issues through Python code development, employing problem-solving techniques to enhance efficiency. Utilized various AWS tools to troubleshoot and resolve problems, demonstrating an ability to integrate cloud-based solutions effectively.Data Science Intern
9/1/2020 - 11/1/2021
Developed data pipelines and implemented data visualization solutions using Python and Tableau, among other tools, to support the Design team. Executed data scraping tasks from governmental platforms utilizing Python, ensuring reliable data extraction. Conducted technical project reviews in the data science domain to drive effective solution development. Explored, reviewed, and tested NLP techniques for processing legal documents. Main tools and frameworks applied included Python, Streamlit, Selenium, Matplotlib, Seaborn, MongoDB, Pandas, NLTK, Tableau, and Git.
Physics at Federal University of Rio de Janeiro
2017 - 2022Artificial Intelligence at Pontifical Catholic University of Rio de Janeiro
2023 - 2025Machine Learning and Artificial Intelligence at Pontifical Catholic University of Minas Gerais
2022 - 2023
AWS Serverless Development at Udemy
1/1/2023Python Object-Oriented Programming at LinkedIn
1/1/2023Git at LinkedIn
1/1/2023AWS Cloud Quest: Cloud Practitioner at Amazon Web Services (AWS)
1/1/2023Advanced Python at LinkedIn
1/1/2022Python 3: Advanced Object-Oriented Programming at Alura
1/1/2021Python 3: Introduction to Object-Oriented Programming at Alura
1/1/2021Git and GitHub at Alura
1/1/2021Machine Learning Formation at Alura
1/1/2021Advanced Machine Learning Formation at Alura
1/1/2021
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