Gabriele Brunini

As a Data Scientist trainee at Vontobel, I develop and implement machine learning models for legal and compliance data, enhancing data-driven decision-making processes.

Investigated automating the classification of polysomnography into different sleep phases using machine learning models, focusing on creating robust algorithms for diverse populations.

Worked on data collection, processing, and post-processing applications under the Center for Legal Data Science, utilizing various libraries and managing Linux servers.

Assisted students in coding issues and answered questions related to blockchain lectures, enhancing their understanding of smart contracts and programming.

Managed multiple student groups, assisting with algorithm implementation tasks and evaluating their work at the end of the semester.

Collaborated on a project involving regex-based reference detection and text extraction from PDFs, supporting PhD researchers in their work.

Developed ETL processes for data migration from legacy databases to data lakes, and created reporting processes for a media company.

Extracted and cleaned raw data from databases, building a recommendation system to model user preferences and suggest products.

Completed a Master of Science in Data Science, focusing on data analysis, machine learning, and data-driven decision-making. Engaged in various projects and research under prominent professors, enhancing practical skills in data science applications.

Participated as a special student in Computer Science, gaining exposure to advanced topics and research methodologies in the field.

Earned a Bachelor of Science in Economics, Management and Computer Science, integrating economic theory with practical computer science applications.

Engaged in an exchange program, broadening academic and cultural perspectives while studying various subjects related to data science and economics.