🌷 DATA, CURIOSITY & A LITTLE PINK
Data Analyst · Analytics Engineer
Turning messy data into clear stories and insights that help people.
SQL, Python, R & a curious mind 🐱
Always learning. Always happy to connect.
01 · About
“Built small. Thinking big.”
I’m Mia Tran—a 5'1" data enthusiast with a big heart, a people-first mindset, and occasional, unpredictable bursts of energy :) An aspiring analytics engineer, I love both turning messy data into a clear story and building the pipelines and workflows that make those stories possible. I care about how data can help people—not just what the numbers say. Curious by nature and a quick learner, I’m open to new challenges and always finding little ways to grow, in my work and in everyday life.
02 · Background
Spinelli Center for Quantitative LearningCurrent
FPT IS
VNPT
Smith College Development Research Team
Viettel Telecom
2023 - 2027
Bachelor Degree
Smith College
Data Science & Quantitative Economics (double major)
Jan 2026 - Jun 2026
Study Abroad
University College London (UCL)
2020 - 2023
High School Diploma
Hanoi-Amsterdam High School for the Gifted
03 · Skills
Python
MySQL
R
Snowflake
dbt
Fivetran
Airflow
Tableau
Power BI
Excel
pandas
NumPy
scikit-learn
TensorFlow
Git
DBeaver
Jupyter Notebook04 · Projects
Data Analyst | Analytics Engineer
An analytics engineering project using daily bike-sharing data, with Python for ingestion, DuckDB for storage, and dbt for data transformation, analysis-ready tables, and data quality testing.
Data Analyst
This project analyzes Skytrax airline passenger reviews to uncover the key factors influencing customer satisfaction and builds a machine learning model
Data Analyst
A Mode dashboard analyzing Spirit Airlines customer satisfaction using Skytrax review data, with insights into service quality, traveler types, seat classes, and trends over time.
Exploratory data analysis of Philadelphia’s Indego Bike Share (2020–2025) using Python. The analysis includes data cleaning, visualization, and insights into bike usage patterns, popular stations, and seasonal trends.
Root-cause analysis of insurance complaint dissatisfaction and processing bottlenecks — star-schema ETL, 10 data-driven questions, and quantified recommendations to improve customer satisfaction.
My team and I designed and developed the disasteRs R package for visualizing and analyzing the trends, frequency, and impacts of natural disasters globally, with a specific focus on Southeast Asia using the EMDAT disaster data database.
05 · Contact
If you have any questions or concerns, please don't hesitate to contact me. I am open to any work opportunities that align with my skills and interests.