Inês Silva

Led a data transformation and transparency project, delivering client-facing datasets across multiple domains. Partnered with clients to gather requirements and define data structures, business rules, calculations, and reporting needs.

Developed machine learning solutions to extract insights from structured and unstructured data, including sentiment analysis to support data-driven decision-making. Delivered Power BI dashboards and KPI reporting after gathering business requirements with operations teams and clients.

Partnered with senior stakeholders to define KPIs, deliver dashboards, and provide data-driven insights for business and marketing performance. Used advanced analytics, segmentation, and behavioral analysis to improve targeting, conversions, and customer engagement.

Contributed to a datathon project by using machine learning algorithms to classify travellers. Worked on delivering patterns and insights aligned with the challenge goals.

Completed an AI master dissertation internship focused on anomaly detection in pet behavioral data using an unsupervised machine learning approach. Applied data science methods to identify patterns in the dataset.

Worked as a Junior Processing Operations Officer, supporting processing operations during the role period.

Activities and societies: Pertinent projects: tourism insights & monthly guest forecasts; ML document quality classification; NLP sentiment in audiobook comments; Bayesian Networks for lending.

Master’s in Data Analytics at Faculdade de Economia da Universidade do Porto. Completed projects including tourism insights and forecasting, document quality classification, sentiment analysis on audiobook comments, and Bayesian network modeling.

Bachelor’s degree in Economics at Faculdade de Economia da Universidade do Porto.

Erasmus exchange at Solvay Business School of Economics and Management as part of the QTEM Network (ULB).