Emily (Yujia) Li

Phone: 469-***-**** E-mail: ad1ami@r.postjobfree.com LinkedIn: https://www.linkedin.com/in/yujia-emily-li/ PROFILE

Masters-level biostatistician with solid training in theoretical and applied statistics, broadly interested in data science and utilization of statistical method for public health and biomedical data. QUALIFICATIONS & SKILLS

• Programming: R, SAS (BASE, STAT, MACRO, SQL), LaTeX, Python, Stata, MATLAB, and nQuery.

• Analysis Techniques: model development, data cleaning, data wrangling, data visualization, exploratory data analysis, web scraping, metadata analysis, random sampling, simulations, hypothesis testing, LASSO/Ridge regression, Principal Component Analysis

• Develop and review Statistical Analysis Plan (SAP), statistical consulting

• Hands-on experience in data analysis execution results interpretation, protocol reviewing and report writing. EDUCATION

University of North Carolina at Chapel Hill, Chapel Hill, North Carolina December 2023 Master of Science in Biostatistics

• Relevant Coursework: Probability and Statistical Inference, Intermediate Statistical Methods, Intermediate Linear Model, Working with Data in a Public Health Research Setting, Applied Longitudinal Data Analysis, Introduction to Survival Analysis, Introduction to Statistical Computing and Data Management, Analysis of Categorical data, Epidemiology, Intro to Public Health Dallas Baptist University, Dallas, Texas May 2020

Bachelor of Arts in Mathematics, Minor in Finance.

• Relevant Coursework: Linear Algebra, Probability & Statistics, Elementary Foundations of Math, Computer Science and Programming

EXPERIENCES

Graduate Research Assistant at UNC Center for Environmental Health and Susceptibility, Chapel Hill, NC 2023-present

• Helped investigators with 2x2 Cross-over trials with statistical design and analysis, by conducting analysis of covariance approach to two baseline responses and the treatment effect.

• Conduct sample size and power calculation and assist with study design for grant proposals. Predict Lung Cancer Remission, Capstone Paper, UNC, Chapel Hill, NC May 2023

• Separated a large dataset into training, validation, and test sets to train a logistic regression model, then used AUC to choose the best model; used sensitivity and specificity to assess model prediction accuracy. English teacher at Longre English Training center, Qingdao, CHINA Sept 2016 - Oct 2017

• Instructed high school and college students on International English Language Testing System (IELTS) exam material and structure through practice problems and sample tests PUBLISHED WORK

Li, Yujia. Identifying Best Predicting Model For Lung Cancer Remission. 2023. https://cdr.lib.unc.edu/concern/masters_papers/sf268f84t?locale=en REFERENCES

Jianwen Cai Cary C. Boshamer Distinguished Professor ad1ami@r.postjobfree.com Haibo Zhou Professor ad1ami@r.postjobfree.com