Data Scientist & AI Engineer

I am a highly accomplished Data Scientist and AI Engineer with over 3 years of experience in applied AI projects, spanning from conception to production. My expertise lies in Generative AI, including large language models (LLMs) and retrieval-augmented generation (RAG), as well as the development of intelligent agents. I have a proven track record of transforming complex data into actionable solutions that drive business value.

I am proficient in Python, SQL, Machine Learning, Natural Language Processing (NLP), and Computer Vision, with hands-on experience working in cloud environments such as AWS and Azure. My strong foundation in statistics enables me to guide model improvements and make informed product decisions. I am adept at taking AI models from prototype stages to full production deployment while continuously evaluating their performance.

In my current role at CESAR, I have led projects that convert unstructured safety reports into predictive risk intelligence dashboards, helping technical teams proactively identify and prevent workplace hazards. I engineered a computer vision lip-mapping system that won the SXSW Innovation Award, enabling visually impaired women to apply makeup more efficiently.

Previously, I worked as a Research Fellow at the Institute of Systems and Robotics, where I developed machine learning algorithms to optimize 3D printing processes, significantly reducing waste and calibration time. I also mentored undergraduate students, supporting their capstone projects and technical integration.

Earlier in my career, I served as a Data Analyst at the University of Aveiro, where I quantified the financial impact of cycling growth on municipal budgets and developed an interactive web simulation tool to support economic planning. I am passionate about leveraging data science to solve real-world problems and continuously expanding my skills in AI and machine learning.