Hello, I'm Mia Vo.
Data Analyst


I'm passionate about using data to drive impact. After earning my degree in Data Science and Statistics from Miami University, I’ve gained hands-on experience across research, industry, and higher ed — from supporting research studies to analyzing clinical trials data. Now, as a Data Analyst at the University of Toledo, I build and maintain Power BI reports and modernize legacy systems using Oracle SQL. Whether it’s education, healthcare, or beyond, I’m always excited to explore new challenges where data can make a difference.

My Resume
Google Scholar

Education

2020-2024
Miami University
Bachelor of Science in Data Science and Statistics
Minor in Computer Science

Related Coursework
Statistical Programming & Methods (SAS, R): Inferential, Regression, Experimental Design, Multivariate Methods.
Database System/Big Data (SQL, Databricks, Oracle)
Data Visualization (PowerBI, SAS, R, rShiny)
Data Structures and Algorithms (Python, Java)

Experience

    Over 3+ years of experience working with data. 
    My expertise is applying data science to 
    various fields, including healthcare and 
    education. I collaborate with clients to 
     understand their specific needs, then 
    conduct in-depth analysis and build 
    visuals to deliver effective solutions 
    that meet their requirements and bring 
    about positive changes. 
 
    Please refer to my resume below for details.

Linkedin Download My Resume
Jun 2024 - Present
Data Analyst
The University of Toledo
    ➤   Developed 50+ Power BI reports to monitor financial transactions & 
 budgets, students’ registrations and performance, etc. 
    ➤   Automated university’s reporting pipelines and migrated 40+ legacy 
 SAP Crystal Reports using Oracle SQL and Microsoft PowerBI 
 Report Builder, eliminating manual SQL queries and data processing. 
    ➤   Rebuilt a system of PowerBI reports for Health Science College to 
 automate input filtering, eliminating manual .NET coding requirements.
Sep 2023 - Jan 2024
Data Science Intern
Medpace
    ➤   Developed advanced SQL queries in Snowflake & integrated queries 
 into PowerBI dashboards to automate analysis of enrollment 
 patterns, streamlining process on studies’ performance deliverables. 
    ➤   Developed interactive visuals in R or RShiny for analysis of 
 sponsors’ proposals, offering insights for proposal strategies. 
    ➤   Designed and executed a PowerBI app through intensive ETL process 
 using Snowflake SQL for bid defenses. 
    ➤   Conducted in-depth analysis of sponsors’ proposals (enrollment 
 modeling, feasibility analysis, sites & countries selection, etc.) 
 for proposal strategies, offering insights into site recommendations, 
 global study locations, & potential competitions.
May 2023 - Aug 2023, Jan 2024 - May 2024
Data Analytics Intern
Westfield
    ➤   Conducted sentiment analysis on customer interactions, identifying 
 sentiment distribution & customer segmentation to enhance satisfaction 
    ➤   Consolidated data from billing, claims, etc., using Tableau 
 to detect revenue loss, cost drivers, & profitability trends.  
    ➤   Utilized R, SQL and analysis techniques (diagnostic, time series, 
 etc.) to track agent performance & report KPIs, enhancing team 
 responsiveness and optimizing business processes by 20%.
May 2022 - Present
Statistical Analyst
Consulting Center - Miami University
    ➤   Conducted analysis on diverse datasets (Neuronal Phases, Linguistics, 
 Chronic Cough Study, etc.) for over 50 clients’ research papers and 
 theses by processing data and applying complex statistical methods 
 (Fisher’s Exact, ANOVA, etc.). 
    ➤   Co-authored three research studies on the effectiveness of a 
 “Minimize Risk, Maximize Life” course administered by Envision 
 Partnerships, Ageism among Korean dental hygiene students, and the 
 effect of Postures among students

Portfolio

EHR-Based Stroke Risk Prediction

Performed data cleaning, feature engineering, and exploratory analysis on hospital EHR data to support stroke risk prediction. Evaluated multiple models using cross-validation and hyperparameter tuning to improve performance, and analyzed key predictors to identify high-risk patient groups and support clinical decision-making.

GitHub
EHR-Based Stroke Risk Prediction
Hospital Readmission Prediction

Hospital Readmission Prediction

Conducted data preprocessing, feature engineering, and evaluated multiple models (logistic, elastic nets, random forests, and neural networks) using cross-validation and hyperparameter tuning to predict hospitals readmission, then assessed the importance of variables to gain insights and develop strategies for reducing readmission rates.

GitHub

American Bar Association Client Analysis

Identify trends and assess customer satisfaction in the legal services industry through ABA's raw data. The research explores customer demographics, question categories, sentiment analysis of conversations, and the determinants of commonly asked questions. Machine learning techniques, such as elastic net, random forests, and neural networks, are employed to develop a robust classification model that predicts the most popular question categories based on relevant predictor variables.

GitHub
American Bar Association Client Analysis
Digest of Education Application

Digest of Education Application

This application analyzes trends in education through the years in 50 US states. The app was made with RShiny. Full user guide can be found in the GitHub.

Launch Application

Spotify Predictions

This program was built to train and create a model that predicts Spotify popularity scores for 70K tracks using 23 known predictor variables from raw RData. Full user guide on GitHub.

GitHub
Spotify Predictions
Movies Recommendation

Movies Recommendation

This application takes 14 million movies tags and evaluates 27 million user ratings associated with 58,000 movies, then suggests an input number of movies based on the input genre with users’ preferences (rating scores, year released). User guide on GitHub.

GitHub

Publications

Kwon, J. H., Hughes, M., Vo, A., Park, J.-R., Kim, D. R., & Kang, K.-H. (2025). Are you anxious about aging? Unpacking the roots of ageism among Korean dental hygiene students. Educational Gerontology, 1–11. https://doi.org/10.1080/03601277.2025.2500724

Role: Statistical Analyst / 3rd Author
View Publication

Orwig, W., Bellaiche, L., Spooner, S., Vo, A., Baig, Z., Ragnhildstveit, A., Schacter, D. L., Barr, N., & Seli, P. (2024). Using AI to generate visual art: Do individual differences in creativity predict AI-assisted art quality? Creativity Research Journal, 1–12. https://doi.org/10.1080/10400419.2024.2440691

Role: Research Analyst / Author
View Publication

Kwon, J., Hughes, M., & Vo, A. (2023). Association between anxiety about aging and ageism toward older adults among Korean dental hygiene workforce. Innovation in Aging, 7(Supplement_1), 835–836. https://doi.org/10.1093/geroni/igad104.2694

Role: Statistical Analyst / 3rd Author
View Publication

Nguyen, M., Vu, D., Vo, A., Liang, L., and Giabbanelli, P. J. (2023) Preserving Simulation Insight While Removing Data: Verification of Compressed Simulation Traces via Machine Learning Annual Modeling and Simulation Conference (ANNSIM), Hamilton, ON, Canada, 2023, pp. 345-356

Role: Author
View Publication

Gnanabharathi, B., Fahoum, S.-R. H., & Blitz, D. M. (2024, June 27). Neuropeptide modulation enables biphasic internetwork coordination via a dual-network neuron. eNeuro. https://pmc.ncbi.nlm.nih.gov/articles/PMC11211724/

Role: Statistical Analyst
View Publication

Simonsen, R. (2023). Exploring similarities in 'seem' constructions with experiencers in English and Spanish. Language, 99(1), e18–e34.

Role: Statistical Analyst
View Publication

Contact Mia

Profile Picture

Phone Number

513-372-5297

Email

miavo2268@gmail.com



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