Zining Qi

I am a first-year master student of biostatistics in School of Public Health, Columbia University Irving Medical Center. I received a Bachelor degree from Indiana University in 2021, where major in Finance and minor in math and statistics. I have spent about two years during undergraduate in statistical projects. Now, I am interested in statistical genetics and computational biology in genetics.

The PDF version of resume is here.

EDUCATION BACKGROUND

Indiana University, Kelley School of Business (2017.08 - 2021.12)

GPA 3.925/4.0
Majors: Finance
Minors: Mathematics, and Statistics
Rewards: University Division of Highest Distinction
Selected Coursework:Technology and business analyses, Data Modeling and Inference, Introduction to computers and programming, Exploratory data analysis, Introduction to differential equation, Introduction to Biostatistics, Probability, Math Analysis

Columbia University, CUIMC, School of Public Health (2022.09 till date)

Majors: Biostatistics
Selected Coursework: Biostatistics Method, Probability, Data Science, Epidemiology

PROJECT EXPERIENCE

NBA Wikipedia Data Scraping Using Python

  • Scraped more than 1000 NBA related data points from more than 100 Wikipedia webpages using python
  • Automated scraping process by regular expression; performed data cleaning and verification using pandas
  • Performed descriptive and inferential data analyses including time series analysis, regression and visualization

Exploratory Data Analysis on Medical Appointment No Show data Using R

  • Performed data visualization including scatter plots, line plots and correlation charts to analyze the relationships among more than 100,000 observations and proposed valuable questions worthy exploring
  • Split the dataset into 3 folds using cross-validation for training and testing
  • Employed multivariable linear regression and logistic regression model to fit the data points

Applied Linear Regression Analysis on Seoul Bike Data Using R

  • Applied power transformation, stepwise model selection, non-constant variance model, Ridge Regression, and Lasso Regression to fit the dataset.
  • Utilized RSS, residual plot, influence analysis, AIC, BIC as selection criteria to perform model selection.

CAMPUS EXPERIENCE

Research Assistant - Kelley School of Business

  • Used STATA to analyze a dataset containing all career paths of elite engineers in the U.S.
  • Used STATA codes instead of insert tools to cleaning data, including renaming variables, dropping meaningless data points, transforming variables, and adding new variables.
  • Merged and grouped the variable “wage” by other variables, such as state, year, and industry.
  • Created csv files and merged them into one STATA dataset.
  • Used codes to match each data point in the dataset with the categories in csv files.

Teaching Assistant - Introduction to Accounting, Kelley School of Business

  • Tutored students and proctored exams.

PROGRAMMING

Skilled in Python, R, STATA