• Develop and maintain proprietary credit risk model to predict risk of loan applications with clustering and boosting techniques, improve performance by 50% over the 1st generation model. Deploy the model on AWS for fast and simple risk scoring and reason codes generation for the underwriting team. • Deploy a cash flow analysis tool on AWS with our engineering team to automatically analyze applicant's cash flow position, quickly feeds result to credit risk model and underwriters, drastically improve operation efficiency. • Utilize text mining and Optical Character Recognition (OCR) on Python to extract information from unstructured spreadsheet and PDF files, conduct risk analysis based on above information and facilitate underwriting process. • Build and visualize loss curve report, conduct funnel analysis and vintage analysis using R and Python. • Integrate SQL database, Salesforce platform and various data sources to feed operational report regularly. Create dashboards on Salesforce with joined reports to visualize leads and deals tracking.

Forepont Group LP | Jul 2018 - Sep 2019

Junior Analyst

database and preset queries in Python that cleaned web tables for easier access to investor information and better adoption by the investment team. • Developed Macros in Excel that automates the calculation of revenue projection model and return on investment, produced pitch presentation deck for future investors, visualized NPV models using Matplotlib in Python. Successfully introduced 2 incubation investments. • Implemented performance analysis of ongoing investment using Proc SQL in SAS and Tableau, developed a pipeline to build reports in dashboard for better visibility of post-investment reviews, worked with investment team to optimize the process. • Built Macro in SAS to automatically update CSV files and generated new reports automatically for regular supervision.

Friendly Senior Living | Jan 2018 - Jun 2018

Data Analyst (Practicum)

• Extracted and cleaned raw data provided by client (a local nursing home) into quantitative data on Python. • Used multiple machine learning models in a pipeline to determine the attributes of high-risk individuals and prevent falls of senior citizens who reside in the facility, recommend the best performance model to our client. • Visualized via Tableau and PowerPoint and presented and interpreted the project result to our client, achieved 80% accuracy with only 106 observations and over 800 features.

My Education

Take a look at my formal education

Master of Science - MS, Business Analytics(STEM Certified)University of Rochester - Simon Business School | 2018

Bachelor of Science (BS), Economics and AccountingPurdue University | 2017

Bachelor of Science (B.S.), Economics中國農業大學 | 2017

About Me

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