Yuanpeng Jia

OPT STEM Philadelphia, PA +1-434-***-**** ad3bvk@r.postjobfree.com

EDUCATION

University of Pennsylvania Aug. 2022- Expected May. 2024 Master of Science in Data Analytics and Social Policy (GPA 3.93, School Scholarship) Philadelphia, PA University of Virginia Aug. 2020- May 2022

Bachelor of Arts in Statistics (GPA: 3.72/4.0) Charlottesville, VA Penn State University Aug. 2018- May 2020

Bachelor of Arts in Finance (GPA: 3.91/4.0) State College, PA Key Modules: Big Data Analytic, Practical Machine Learning, Practical Data Science, Applied Linear Models, Applied Time Series, Nonparametric statistics, Experimental Design, Intermediate Microeconomics, etc. INTERN EXPERIENCE

Twitter Jul. 2023- Sept. 2023

Data Analyst Intern Hongkong, China

● Engineered Python solutions for data preprocessing, cleaning, and analysis focusing on user behavior and engagement metrics, utilizing Matplotlib/Seaborn and Tableau for impactful data visualization.

● Conducted user segmentation and behavioral analysis leveraging Machine Learning algorithms such as Gradient Boosting and Random Forest to understand user demographics and preferences.

● Orchestrated and analyzed A/B tests and experiments using Python to assess the impact of changes on user behavior, facilitating data-driven decision-making.

Roland Berger May. 2022- Sept. 2022

Consulting Analyst Intern Beijing, China

• Synthesized industry reports and market data to perform statistical analysis, generating comprehensive visualizations to understand the market landscape.

• Forecasted 2023 Chinese parking market trends and authored a detailed report on the Chinese intelligent parking market for the esteemed Italian enterprise CAME.

• Devised strategic investment recommendations for Alibaba by conducting an in-depth sales and profit analysis of five major prominent Chinese pet food brands.

China Everbright Bank May. 2021- Aug. 2021

Data Analyst Intern (Risk Control) Beijing, China

• Analyzed credit card transaction data (140 million) over three years, segmenting the dataset and incorporating a negative sample rate of 1.5%, using Python.

• Developed comprehensive data characteristics based on current transaction volumes and derivative variables, utilizing Information Value (IV) and missing rate criteria for initial hypothesis validation.

• Implemented a highly efficient credit scoring methodology using Python and XGBoost, assisting the bank in effectively managing diverse customer profiles.

RESEARCH/PROJECTS

Machine Learning Project on Diabetes Prediction Philadelphia, PA Jan. 2023- May. 2023

• Conducted comprehensive data wrangling and preprocessing using Python, addressing challenges such as missing values, class imbalance, and scaling through normalization, imputation, and under-sampling.

• Employed Seaborn for effective data visualization, utilizing different graphs for exploratory data analysis (EDA).

• Compared various machine learning algorithms, selecting Adaboost for its high accuracy in predicting diabetes. Machine Learning Project on Predicting the Likelihood of Car Accidents Philadelphia, PA Jan. 2023- May. 2023

• Led a three-person team to preprocess a large dataset of 2.8 million data points, utilizing Python and selecting a random sample of 100,000 observations for system efficiency.

• Applied unsupervised machine learning (PCA) for feature reduction and compared multiple supervised ML algorithms to predict accident severity and likelihood.

• Integrated results obtained from all machine learning algorithms into a table and visualize the results in Tableau for performance comparison.

SKILLS

● Technical Skills: Python, MySQL, PostgreSQL, R, Tableau, Power BI, Mircosoft Office Suites

● Language Skills: English, Chinese

● Soft Skills: Communication, Adaptability, Teamwork, Time Management, Leadership