Laura Novaes

I work in the fields of Artificial Intelligence and Data Engineering, developing data pipelines and architectures that transform large-scale data into analytical assets and AI-driven solutions for business applications. I have more than 4 years of experience in data, working with Big Data, data engineering, and machine learning, using technologies such as Python, PySpark, SQL, AWS, and Airflow to build scalable and automated data pipelines. Currently, I work as an AI Engineer at Banco Inter, in the credit and collections area, where I develop data and AI pipelines for analyzing customer interactions in voice and text channels. My work involves large-scale data ingestion and processing, integration of multiple Big Data sources, and the creation of structured analytical datasets that feed Artificial Intelligence models, generating quantitative and qualitative insights that support strategic decision-making and improve customer experience. I also operate at the intersection between technical and business teams, translating strategic needs into data and AI-driven solutions, automating processes, and structuring data assets for consumption by analytical models and AI agents. In addition to data engineering, I have experience in Data Science, performing statistical analyses and predictive modeling using tools such as Pandas, PyTorch, TensorFlow, XGBoost, pmdarima, and Scikit-learn. I have also developed data-driven applications using Streamlit, as well as prototypes and proofs of concept using both real and open-source datasets across multiple sectors, including finance, legal, and healthcare. I am fluent in English and have advanced proficiency in Spanish