Cheng Yang
San Diego,CA
Overview
13
13
years of professional experience
1
1
Certification
Work History
Data Scientist
Purpose Financial
10.2021 - Current
- Analyze data to identify and understand potential risks and outcomes of decisions, and conduct statistical techniques to predict and evaluate credit risk within loan portfolio.
- Apply programming and analytical techniques to analyze credit data, and develop processes for gathering and storing data for future analytic projects.
- Ensure risks associated with business activities are effectively identified, measured, monitored, and controlled.
- Develop Predictive models for customer response for soliciting prospective customers to offer credit lending.
- Employee of the Month (Dec, 2023)
Graduate Teaching Assistant
Clemson University
08.2019 - 08.2021
- Hold in-person and online Laboratory course of Statistical Method sessions for about 80 students each semester.
- Grading, proctoring, and providing office hours.
Senior Accountant
Hangtian Hengxing Precision Electromechanical
08.2010 - 07.2015
- In charge of tax, cost and expense accounting, preparation of various financial statements, statistical work of both internal and external financial data, fixed assets accounting, current account calculation and clearing, etc.;
- Premium & Advanced Individual of Statistics in Xi'an High-tech Zone for three consecutive years, 2011-2013
Education
Master of Science - Mathematics
Clemson University
Clemson, SC08.2021
Bachelor of Arts - Accounting
Northwest University
Xi'an, China06.2010
Skills
- Programming: R, Python, SAS, Snowflake, SQL, Matillion, MATLAB;
- Tools: Tableau, JMP, Git, MS Office; Language: Chinese (Mandarin)
Projects
Prediction of Response Rate of Direct Mail. (Python) 2023/03
Prediction of Whether Customers will be Default on Loan. (R Studio) 2021/08
- Predict if a customer will be default on loan by comparing Logistic regression, Random forest, and SVM models;
- Try to resolve the imbalance data issue by using oversampling and adjusting weights for each model.
Modeling Unobserved Heterogeneity in (car insurance) Claim Counts. (R Studio) 2021/01-2021/05
- Modeling claim counts of a car insurance company by zero-inflated and k-finite mixture models to resolve the problem of over-dispersion and excess of zeros;
- Explore whether resolving the problem of unobserved heterogeneity requires a richer structure for the selected data set.
Certification
- SAS Certified Specialist: Base Programming Using SAS 9.4
Timeline
Data Scientist
Purpose Financial
10.2021 - Current
Graduate Teaching Assistant
Clemson University
08.2019 - 08.2021
Senior Accountant
Hangtian Hengxing Precision Electromechanical
08.2010 - 07.2015
Master of Science - Mathematics
Clemson University
Bachelor of Arts - Accounting
Northwest University
- SAS Certified Specialist: Base Programming Using SAS 9.4
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