Technical Skills

My work combines epidemiology, data science, and public health research with a strong emphasis on applied analytics, reproducibility, and communication.

Programming & Tools

Languages

R

SQL

SAS

Python

SPSS

STATA

R & SAS primary; Python actively developing

Reproducibility & Reporting

Quarto

Git / GitHub

R Shiny

R Markdown

Data & Databases

EHR (Epic, Cerner)

BRFSS / NHANES / SEER

REDCap

Clinical datasets

CDC surveillance data

Analytics & ML

Regression modeling

Survey-weighted analysis

Machine learning

NLP / LLMs

Causal inference

Data visualization

Domain Expertise

Public Health & Epidemiology

Epidemiologic study design

Real-world evidence (RWE)

Health disparities

Cancer epidemiology

Observational studies

Clinical & Industry-Facing

Real-world data (RWD)

Clinical trial design

Diversity & inclusion in research

IRB & regulatory compliance

Stakeholder communication

Languages

Spoken Languages

Spanish — native

English — fluent

Selected Awards & Recognition

Awards

AUC Data Science Initiative — Curriculum Development Award (2024)

FIU Three Minute Thesis — Top 10 Finalist (2023)

FIU Outstanding Graduate Teaching Assistant Nominee (2023)

C.V. Starr Scholarship — Florida International University

Strengths I Bring

Beyond technical tools, I bring a strong ability to connect analytic work with meaningful public health questions. I enjoy translating complex data into clear insights, collaborating across disciplines, and designing work that is rigorous, reproducible, and useful in practice.