- Languages: Portuguese (Native), English (Advanced)
- Programming Languages: Python, C
- Databases: PostgreSQL, MySQL
- Machine Learning: Pandas, Scikit-learn, Numpy, CatBoost, XGBoost, LightGBM, Keras, PyTorch, Tensorflow, NLTK, Spacy, RegEx, Gensim, Transformers, Scipy, Optuna
- MLOps: FastAPI, Streamlit, Flask, PyTest, Unittest, Docker, MLflow, AWS, Git, Requests, GitHub Actions, CI/CD, Loguru
- Data Visualization: Seaborn, Matplotlib, Plotly
- Data Scraper: BeautifulSoup4, Selenium
Junior Machine Learning Researcher @ CPQD
April 2022 - Present | Campinas, Brazil · Remote
About the company: CPQD is the largest research and development center in Latin America, focused on developing Proof of Concept (PoC) for information and communications technology solutions for a wide range of sectors.
- Developed a deep learning model that raised the accuracy of the existing voice activity detection model by more than 20% and decreased the false positive rate by 12%, improving the quality of the business's speech recognition product.
- Created a new supervised sentiment analysis model using artificial neural networks, offering useful information about users satisfaction with the client's products.
- Engineered a novel text classification model that classifies user reviews of the client's products using a tree-based algorithm, offering insightful information to support business decision-making.
- Designed an unsupervised clustering model that tracks the condition of internal combustion engines over time to identify early failures, which produced a paper submitted to an international automotive engineering symposium.
- Utilized machine learning and signal processing techniques to implement a C-based solution integrated into Arduino hardware to perform the sound event classification task, achieving near-real-time responses and high accuracy.
- Created a new supervised machine learning model for the classification of dental prosthesis quality tasks in an Industry 4.0 case scenario, offering insights about production batch quality while aiming to reduce the number of faulty prostheses.
- Helped and assisted in the development of a machine-learning model to classify sleep stages using only heartbeat data collected via an electronic wristband.
- Wrote documentation, patents, software registration, and papers of the developed models.
Junior Data Scientist @ SMARKIO (acquired by D1)
March 2021 - March 2022 | Itajubá, Brazil · Remote
About the companies: SMARKIO was a company that specialized in implementing chatbots according to the company's needs, which was later acquired by Direct One (D1), a company that develops technologies using Artificial Intelligence to personalize and expand engagement between customers and companies.
- Developed new models using machine learning, deep learning, and natural language processing techniques for sentiment analysis, clustering, and topic classification tasks to gain insights into the performance of clients' chatbots.
- Enhanced processing speed and memory by more than four times through the refinement of the data acquisition and preprocessing stage through the use of multiprocessing and simpler function design.
- Improved the company’s best communication channel recommendation algorithm by employing a statistical, rule-based method-only approach, leveraging the response rate and customer engagement by more than 15%.
- Provided insightful data visualization and analytics reports that aided the curatorial team in making business decisions.
Intern Python Developer @ B2ML
January 2021 - March 2021 | Itajubá, Brazil · Remote
About the company: B2ML is a company that offers services to leverage its clients' businesses, developing, deploying, and maintaining complete solutions, from web platforms to digital banks and IoT systems with AI.
- Updated a web platform aimed at reconciling company receivables by creating use cases for new clients and improving already existing ones.
Master of Business Administration (MBA) in Artificial Intelligence and Big Data @ University of São Paulo (USP)
July 2022 - October 2023 | São Carlos, Brazil
The MBA covers the most diverse topics within the area of artificial intelligence and big data, such as: Python, R, statistics, SQL, Machine Learning, Deep Learning, Data Mining and Visualization, Data Governance and Management, Big Data, Natural Language Processing and Data Analysis.
The theme of my end-of-course work was "Speech Emotion Recognition using Deep Learning and Wavelet Transform" and was done under the supervision of Dr. Prof. Alessandra Alaniz Macedo.
Bachelor in Computer Science @ Federal University of Itajubá (UNIFEI)
January 2018 - December 2021 | Itajubá, Brazil
- Fellow in front-end development of a unified medical data management platform for the city of Itajubá and the state region (August/2020 - January/2021).
- Participated in programming competitions at college and state region representing UNIFEI (October/2018 - February/2019).
- Worked at byron.solutions, a junior technology and information company located inside UNIFEI, as a WordPress web developer (April/2018 - October/2018).
The theme of my final graduation work was "Comparison of deep learning models in the classification of comments containing hate speech on the Internet" and it was done under the supervision of Dr. Prof. Isabela Neves Drummond.
- AWS Cloud Technical Essentials (Oct, 2024)
- Deployment of Machine Learning Models (Aug, 2024)
- MLflow in Action - Master the art of MLOps using MLflow tool (Jul, 2024)
- Machine Learning Specialization (Jun, 2024)
- Duolingo English Proficiency Certificate (Jan, 2024)
- Mathematics for Machine Learning: Linear Algebra (Feb, 2023)
- Version Control with Git (Feb, 2023)
- Machine Learning Engineering for Production Specialization (Jan, 2023)