YUEXIU (RACHEL) JIN
ac7s61@r.postjobfree.com 718-***-**** linkedin.com/in/yuexiu-jin/
EDUCATION
New York University, Tandon School of Engineering Brooklyn, NY Master of Science in Financial Engineering (GPA: 3.62/4.0) May 2019 Nanjing Agricultural University Nanjing, China
Bachelor of Science in Biotechnology (GPA: 3.7/4.0) Jun 2017
• National Scholarship, Nanjing Agricultural University, 2014-2015
• Top Ten Student Leaders, Nanjing Agricultural University, 2015-2016 PROFESSIONAL EXPERIENCE
QBE North America New York, NY
Risk Analyst Intern Jun 2018-Aug 2018
• Developed a risk rating model to assess small and medium-sized enterprises (SMEs) probability of default (PD) and loss given default (LGD) using Python and Excel. Tested by regional trade credit portfolios.
• Performed fundamental credit analysis on 25 corporate clients to assist the Credit Manager in making conclusions and recommendations on new business opportunities.
• Conducted top-down analysis of oil industry using Bloomberg, include performing sensitivity test between historical insurance premium and oil price using IHS Markit financial services, and presented to senior management.
• Monitored commodity market news and price fluctuations to predict the future changing of company’s credit and new business opportunities. Responsible for commodity part of monthly economic newsletter.
• Automated Excel reporting procedure via VBA, which improved working efficiency by 99.5%. COMPETITION EXPERIENCE
PRMIA Risk Management Challenge Mar 2018
• Conducted a case study about GE after the crisis. Found strategies let GE mitigate its top 3 risks.
• Analyzed the impacts of the Warren Buffet $3B investment in 2008 by calculating probability of default of GE.
• Designed risk governance system for GE to monitor risks. SKILLS AND CERTIFICATIONS
• Computer: Python, R, C++, Excel VBA, SQL
• Certifications: CFA Level III candidate, Bloomberg Market Concepts (BMC) Certification PROJECTS EXPERIENCE
New York University, Tandon School of Engineering Brooklyn, NY Risk Modeling (Python) Spring 2018
• Conducted an in-depth analysis on a dataset about credit card clients to predict credit default with 82% accuracy.
• Fitted logistic regression and classification models to training data, using SVM, KNN and Random Forest. Portfolio Optimization Fall 2017
• Analyzed Statistical features of target stocks and generated variance covariance matrix.
• Constructed maximum return portfolio under Markowitz portfolio theory and tracked performance.
• Calculated portfolio VaR and CVaR using Variance-Covariance, historical, and Monte Carlo method in Excel and R.
• Performed bootstrap simulation to estimate the standard errors of VaR and CVaR. Applied antithetic sampling to reduce the standard error.
CDO tranche loss distribution modeling and visualization Fall 2018
• Calculated CDO loss distribution density function under Vasicek model.
• Created interactive charts of expected losses on a CDO tranche using R Package Shiny and documented by R Markdown ioslides presentation.