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About Me (she/her)

My passion for Mathematics and Statistics has led me into the world of data analysis, where I enjoy uncovering hidden stories within data.

I began my career as a data quality analyst, where I realized the deceptive nature of data and the crucial role of clean data processing. I worked in the quality department at MCI for 4 years to enhance my understanding of data integrity.

Exploring the role of statistics in health has convinced me to pursue further education in Biostatistics at McGill University. During my studies, I delved into causal inference studies and had the opportunity to analyze the National Health and Nutrition Examination Survey (NHANES) data from the Centers for Disease Control and Prevention (CDC). Observing how data analysis can positively impact people's health motivated me to contribute my data skills to public health.

I have gained experiences in data analyzing with R and advanced (bio)statistical methods, including dynamic treatment regimens (DTR), dWOLS, propensity score, and inverse probability weighting for observational studies.

Project 1

Data Analytics (R - Rmarkdown)

Generalized Linear Model (2021)

Project 2

Simulation (R - Rmarkdown)

Causal Inference (2022)

Project 3

Data analytics (R - Rmarkdown - Excel)

NHANES Data (2023)

Project 4

Data Visualization (Tableau)

NHANES Data (2023)