Guomin Peng (Rhoda)

Data Analyst Master Degree Data Science Related Major Purdue University

682-***-**** adf4qj@r.postjobfree.com https://www.linkedin.com/in/rhodapangheadhunter/ https://github.com/rhodapang/rhoda_datascience

About ME – A quick learner who is passion to be an excellent Data Scientist Programming Language: Python

Analytics: R, SQL, Numpy, Pandas, Matplotlib, Seaborn DS Knowledge: Statistical Data Analysis, AB Test, Data Mining, Modelling, Machine Learning

(Supervised Learning: regression and classification; Unsupervised Learning: Clustering and Dimensionality Reduction), Deep Learning

HR Knowledge: Understand Employment Law of United States, Staff management, Compensation Management

Language: Fluent in written and spoken Chinese (Both Mandarin and Cantonese), English Network: Tremendous networking ability (Have 9,900+ connections on LinkedIn) Education

Purdue University 01/2019—May,2020

Master of Open Digital Innovation-Data Science

Shenzhen University 09/2007—07/2011

Bachelor of Science in Human Resource Management

Working Experience

Jun 2020 – Aug 2020 WeiCepts LLC

Position: Financial Data Analyst

Report to: CEO and Founder

Responsibilities:

Build up database for Fannie Mae mortgage data, explore numerical variables and categorical variables in dataset, understand their correlation between those variables

Single Monthly Mortality (SMM) and CPR: calculate them for specific period mortgage loan, explore their relationship against Time in different group and against Economic index

(Unemployment Rate, HPI, FHLMC)

Roll rate analysis depending on delinquency status of each loan

Data preparation, utilizing machine learning models: logistic regression, SVM, random forest, gradient boosting etc. to predict loan with delinquency status exceeding 60 day and 90 days.

Compare different model performance and conduct machine learning model validation Feb 2016 – Nov 2016 Hyper Growth Management Consulting Ltd Position: Recruiter Apr 2013 – Jan 2016 Hui Associates Limited Position: Recruiter