Yasmin Toledo
Epidemiologist (MSc & PhD ongoing at ENSP/FIOCRUZ) working with Real-World Evidence (RWE) and Machine Learning in Healthcare. 6+ years generating evidence in infectious diseases (COVID-19, measles, influenza, arboviruses).
Professional Experience
Research Epidemiologist | AI Champion
Conducts Real-World Evidence (RWE) and Real-World Data (RWD) observational studies for pharmaceutical and life sciences clients. Appointed AI Champion, designing AI agents that optimize scientific workflows and save ~30 hours per project.
Epidemiologist — Hospital Surveillance
Conducted morbidity/mortality analyses, interactive KPI dashboards, and vaccine pharmacovigilance for the 2024 influenza campaign. Automated epidemiological surveillance workflows to reduce response times.
Research Fellow — Measles Risk Stratification
Applied spatio-temporal modeling and WHO risk stratification tools for measles transmission in Rio de Janeiro. Published three peer-reviewed international manuscripts.
Research Fellow — COVID-19 Surveillance Models
Characterized public health surveillance models for COVID-19 and severe acute respiratory syndromes to inform pandemic preparedness and response systems.
Education
PhD in Epidemiology in Public Health
ENSP / FIOCRUZ — Oswaldo Cruz Foundation
MSc in Public Health Epidemiology
ENSP / FIOCRUZ — Focus: Infectious Diseases & Statistical Modeling
BSc in Public Health
Federal University of Rio de Janeiro (UFRJ)
Skills & Technologies
Analytical & Modeling Tools
Methodological Expertise
Languages
Portuguese: Native
English: Intermediate (B1) — Critical reading & scientific writing, daily international team work
Spanish: Intermediate (B1)