Open to opportunities

Tsui-Feng Wu

@tsui-fengwu

Biostatistics and data science researcher specializing in experimental design, statistical modeling, and machine learning.

United States

Message

What I'm looking for

I’m looking for a role where I can apply biostatistics and machine learning to real problems, run rigorous experiments and analyses, and communicate results clearly through reproducible reports that support data-driven decisions.

I’m a graduate biostatistics researcher focused on rigorous experimental design, causal thinking, and statistical modeling. With a GPA of 4.0/4.0, I pair strong technical training with a clear commitment to producing results that others can trust and build on.

In my research work (2024–2026), I design randomized experiments, conduct power analysis and sample-size planning, and analyze outcomes using approaches such as regression, ANOVA, t-tests, mixed models, and time-to-event methods. I’ve presented and authored Quarto/R Markdown reports with annotated code and results for collaborators.

I also translate data into action through supervised learning. For a bank churn prediction project, I performed data cleaning, preprocessing, EDA, and model training (Logistic Regression, KNN, Random Forest), achieving strong discrimination (Random Forest accuracy = 0.86, AUC = 0.85) and identifying key churn predictors (age, membership status, estimated salary).

Beyond modeling, I’ve built reliability through survey and lab work—designing 10+ surveys with strong reliability/validity and mentoring 50+ undergraduates in experimental design and data analysis. I’ve also authored 4 peer-reviewed publications and served as a manuscript reviewer, which fuels how seriously I take technical writing and statistical accuracy.

Experience

Work history, roles, and key accomplishments

Graduate Biostatistics Researcher

The Ohio State University

Jan 2024 - Jan 2026 (2 years)

Designed and analyzed randomized biostatistical research projects, using power analysis, regression, and longitudinal methods to evaluate study outcomes. Built a Python churn prediction model where Random Forest achieved 0.86 accuracy and 0.85 AUC, and produced reproducible Quarto/R Markdown reports with annotated code and results for collaborators.

R Markdown SAS Stata Regression & Moderation Analysis Random Forest Logistic Regression

Education

Degrees, certifications, and relevant coursework

The Ohio State University

Master of Biostatistics (Minor in Bioinformatics), Biostatistics

2024 - 2026

Grade: 4.0/4.0

Activities and societies: Relevant coursework: R for Data Science; SAS Programming; Python & Machine Learning; biostatistical data analysis; regression methods; causal inference; survival & longitudinal analysis.

Pursuing a Master of Biostatistics with a minor in Bioinformatics (GPA 4.0/4.0) with coursework covering biostatistical modeling, regression, survival analysis, and causal inference. Completed graduate biostatistics research projects using R, SAS, STATA, and R Markdown.

LaiOffer

Data Science Certificate, Data Science

2025 -

Activities and societies: Topics included probability theory, Python, data structures & algorithms, machine learning, SQL, A/B testing, and Tableau.

Earned a Data Science Certificate through a 17-week bootcamp emphasizing probability theory, Python, data structures/algorithms, and machine learning fundamentals. Covered SQL, A/B testing, and Tableau.

Alex Data Analytics Bootcamp

Data Analysis Certificate, Data Analysis

2025 -

Activities and societies: Focus areas: Python, SQL, Microsoft Excel, Tableau, and Power BI.

Earned a Data Analysis Certificate focused on practical analytics using Python and SQL. Covered Microsoft Excel, Tableau, and Power BI for reporting and visualization.