Tiago Vaz is a Data Governance Lead with 8+ years bridging computer science, epidemiology and enterprise data strategy across healthcare and consumer goods. He combines a PhD in Epidemiology and an MBA-like executive education with hands-on experience building scalable data pipelines, causal inference for real-world evidence, and governance frameworks for Data & AI at global scale. His background spans technical leadership roles—from building national hospital information systems and coordinating multi-country EHR evidence generation to improving forecasting at Kraft Heinz—showing a rare mix of delivery, policy and research impact. An active contributor to public health modelling (notably extending palliative care features in the widely used neherlab/covid19_scenarios project), he blends open-source development with rigorous validation and UI integration. Based in Utrecht, he is known for translating complex domain requirements into auditable, reproducible data products and for fostering cross-functional teams that accelerate responsible AI adoption.
7 years of coding experience
17 years of employment as a software developer
MBA Executive Business Management Marketing and Related Support Services, MBA Executive Business Management Marketing and Related Support Services at ESPM Escola Superior de Propaganda e Marketing
Executive Education - Organizational Leadership - Leading Change and Organizational Renewal, Executive Education - Organizational Leadership - Leading Change and Organizational Renewal at Harvard Business School
Bacharelado Computer Science, Bacharelado Computer Science at Pontifícia Universidade Católica do Rio Grande do Sul
Executive Certificate in Management and Leadership, Executive Certificate in Management and Leadership at MIT Sloan School of Management
PhD Epidemiologia, PhD Epidemiologia at Federal University of Rio Grande do Sul
English for International Business, English for International Business at University of California, Riverside
Models of COVID-19 outbreak trajectories and hospital demand
Role in this project:
Full-stack Developer
Contributions:13 commits, 7 PRs, 10 comments in 7 months
Contributions summary:Tiago contributed to the project by implementing new features related to palliative care within the COVID-19 model. They modified the core model logic, adding palliative flux calculations and integrating these changes across multiple files, including the model definition, test data, initialization, and UI components. The user also updated the schema and validation rules to accommodate the new palliative care parameters, ensuring data integrity. Their work demonstrates a focus on extending the model's capabilities and improving its user interface.
Models of COVID-19 outbreak trajectories and hospital demand
Contributions:2 PRs, 172 pushes, 11 branches in 2 years 7 months
hospitaloutbreaktrajectoriesdemand
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