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Summary
I’m a self-taught and dedicated professional passionate about Artificial Intelligence. I actively seek out new challenges, stay current with the latest advancements, and work on personal projects to deepen my knowledge. My main areas of interest include Natural Language Processing, Deep Learning, Machine Learning, MLOps, and Python. Currently open to remote or on-site opportunities across Europe as a Machine Learning Engineer or Data Scientist, eligible to work in the EU without visa sponsorship.

Skills
  • Languages: Portuguese (Native), English (Advanced)
  • Data Wrangling, Analysis & Visualization: Pandas, NumPy, PySpark, Matplotlib, Seaborn, SciPy, Plotly, Folium
  • Programming Languages: Python, C, SQL
  • Machine Learning (ML): Scikit-learn (certified), XGBoost, LightGBM, Keras, TensorFlow, PyTorch, Optuna
  • Natural Language Processing (NLP): Transformers, Spacy, NLTK, Gensim
  • MLOps: FastAPI, Streamlit, Flask, Docker, MLflow, AWS (certified), Git, CI/CD (GitHub Actions), Pydantic, PyTest, Unittest, Loguru, Evidently AI, Terraform
  • LLMs & Generative AI: OpenAI API (prompt engineering)

Work Experience

Data Scientist @ Driva

Mar 2025 - Present | Curitiba, Brazil · Remote

As a Data Scientist at Driva, my main achievements include:

• Reduced false positives by 21% and improved accuracy by 14% in an e-commerce classifier model using a tree-based algorithm and a streamlined data pipeline with PySpark, cutting processing time and memory usage by 33%.
• Created a Python/AWS model with Scikit-learn to match LinkedIn profiles to CNPJs (Brazilian company registry), achieving 83% precision, reducing manual effort, and improving a core product.
• Built a machine learning model utilizing Python, AWS, and Scikit-learn to categorize e-commerce websites into relevant segments, helping a client identify new leads and connect with potential customers.
• Used prompt engineering with the OpenAI API to support data labeling and validation, ensuring high-quality datasets for training ML models.
• Served as tech lead for an intern, providing 1:1 mentorship, teaching core data science and AI concepts, guiding model development, and aligning work with business objectives.

Machine Learning Researcher @ CPQD

Apr 2022 - Mar 2025 | Campinas, Brazil · Remote

As a Machine Learning Researcher at CPQD, my main achievements included:

• Improved a voice activity detection system, increasing accuracy by over 20% and reducing false positives by 12%, thus enhancing the performance of the company’s speech recognition product.
• Developed a supervised sentiment analysis model using a combination of artificial neural networks and a tree-based classifier, enabling actionable insights into user satisfaction with client products.
• Engineered a tree-based text classification model to analyze product reviews, providing insights to guide client business decisions.
• Designed an unsupervised clustering model to monitor internal combustion engine conditions and detect early failures. The results led to a paper submission to an international automotive engineering symposium.
• Implemented a C-based sound event classification system, combining ML and signal processing for near real-time inference on Arduino hardware with high accuracy.
• Built a supervised ML model for classifying dental prosthesis quality in an Industry 4.0 scenario, supporting defect detection and improving batch-level production monitoring.
• Collaborated on a model for sleep stage classification, using heartbeat data from wrist-worn devices to enable non-invasive monitoring.
• Authored technical documentation, patent applications, software registrations, and research papers related to the developed models.

Junior Data Scientist @ SMARKIO (later acquired by D1)

Mar 2021 - Mar 2022 | Itajubá, Brazil · Remote

As a Data Scientist at SMARKIO (later acquired by D1), my main achievements included:

• Built new machine learning and deep learning models for NLP tasks, such as sentiment analysis, clustering, and topic classification, enabling performance insights for client chatbots.
• Improved data processing speed and memory efficiency by over 4 times by redesigning the data acquisition and preprocessing pipeline using multiprocessing and simplified functions.
• Improved customer engagement by more than 15% by improving the company’s communication channel recommendation algorithm through a statistical, rule-based approach.
• Delivered data visualizations and analytics reports that supported the curatorial team in data-driven business decision-making.

Intern Python Developer @ B2ML

Jan 2021 - Mar 2021 | Itajubá, Brazil · Remote

As a Python Developer at B2ML, my main achievements included:

• Enhanced a web-based receivables reconciliation platform by developing new client-specific use cases and optimizing existing ones for performance and maintainability.

Education

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.

Selected Certifications