Markets Quantitative Analysis (MQA)Citigroup Global Markets Inc.✔ Developed, maintained, and supported Python analytics libraries for the Global Spread Products Asset-Backed Securities (ABS) Financing and Securitization team, identifying trading opportunities. Enabled daily use via an Excel Add-in for the front office and automated processes in the IT production system. - Python (pandas, numpy, scipy, statsmodels)✔ Built and deployed web-based applications covering both front-end and back-end development. Collaborated closely with traders and structurers to identify requirements, designed intuitive user interfaces, and implemented backend calculations in coordination with the data provisioning team.✔ Developed and implemented Basel and CCAR quantitative models for asset-backed facilities backed by auto and personal loans using Python and MATLAB. Worked with the model validation team to understand validation results and address concerns. Delivered production-level code and compiled executables for the Global Securitized Markets IT team’s monthly model runs.✔ Reviewed and enhanced existing models to ensure they remained fit for purpose. Performed model revalidation, outcome analysis, backtesting, sensitivity analysis, and ongoing performance analysis.✔ Assisted HR in reviewing resumes and conducting interviews for Quant Summer Internship Program.

Enterprise Risk Management ProgramIntro to Quantitative Risk ManagementTeach by Michael Ding✔ Facilitated course content on regression, statistics, bond pricing, calculus, probability, and linear algebra.✔ Conducted weekly office hours, providing tutoring and assistance to around 50 students.✔ Reviewed educational materials, supported lecturers in creating assignments and exams, monitored student progress, and assigned grades.

Master of Financial Engineering ProgramMarket MicrostructureTeach by Dmitry Rakhlin and Tai-Ho Wang✔ Programming language: pythonPackages: matplotlib , numpy , pandas , scipy , statsmodels , scikit-learn✔ Attended classes and graded assignments for students in Master of Financial Engineering Program.

Quantitative Analysis and Technology --- Securitized Products✔ Developed and analyzed the PD model using Logistic Regression and the LGD model using Multiple Linear Regression for CLO collateral performance. Implemented the pricing engine in C++ based on Python prototypes. Collaborated with the model validation team to understand validation results and remediate concerns. Documented model descriptions, outputs, statistical testing, and sensitivity analysis, and limitations.✔ Built and analyzed new quantitative risk models for products traded by the Securitized Products business and ensured their accurate implementation. Coordinated with the market risk managers to ensure that their concerns are appropriately reflected in the models. Evaluated the impact of new models and capital rules.✔ Collaborated with the data, IT, and change-management teams to ensure that methodology changes were appropriately project-managed for implementation.✔ Reviewed and improved existing models to ensure they remain fit for purpose. Ensured all models are adequately documented for both internal and external purposes.✔ Delivered lectures on Fundamental Risk Management in the Quantitative Strategist Internship Program.

Methodologies Group --- Structured Finance Sector✔ Performed model implementation verification on many rating models for their consistency with corresponding methodology and documentations. Used existing MATLAB and Python testing framework while coded a lot of replica models in MATLAB, Excel/VBA and Python for complicated models. Overall verification efforts include code review, test cases design, outcome analysis and documentations review. ✔ Implemented and monitored the existing structured finance models in C++. Discussed the requirements and proposed enhancements with practice analysts. Interacted with model testers to resolve model issues. Documented detailed model specification and change log.✔ Developed new model engine packages in R and user interfaces in R Shiny. Collaborated with Criteria specialists and practice analysts for model details. Trained analysts to use the models and improved the models based on their feedback. ✔ Provided mitigation/management action plans for identified model errors, made recommendations and managed the entire error correction process.✔ Gained insight into many credit scoring, capital, and cashflow models through the process of implementation verification. Key models worked on before: structured finance (CDO Evaluator, Covered Bond Monitor, RMBS and Counterparty Risk model); public finance (Priority Lien Credit Scoring for Muni, Transportation Infrastructure for Muni); insurance (Country Risk model) and financial institutes (Risk-Adjusted Capital for Banks and NBFI)

Model Implementation Center (Quantitative Analytics Research Group)✔ Conducted detailed implementation verification for several credit models as well as accounting heavy models used for ratio adjustments, earnings forecasting or capital. Internship extended to complete two key projects after initial summer term.✔ Built a flexible testing tool in Excel/VBA allowing analysts to test different breaking points for segmentation of financials while seeing the results and distributions for 3,000+ credits instantly. This helped shorten one iteration of testing from a few days to few hours.✔ Contributed to improvements in the Python framework used for data loading and results analysis.

✔ Distinction on Advanced Calculus with Financial Engineering Applications✔ Distinction on Probability Theory for Financial Applications✔ Distinction on C++ Programming for Financial Engineering

Beta Gamma Sigma is the international business honor society that recognizes the most outstanding students of business at institutions accredited by AACSB International - The Association to Advance Collegiate Schools of Business.Students are chosen to be recognized at business schools accredited by AACSB International after having met certain academic criteria. General membership eligibility criteria is as follows:Undergraduate level – top 10%Graduate level – top 20%Doctoral level – after all program requirements have been met

✔ Accurately processed payments on letters of credit between international companies on weekly basis✔ Reviewed letters of credit to ensure company eligibility to obtain sources of funding✔ Transferred client information into the Bank of China database✔ Researched international settlement processes for businesses desiring to import and export in China

✔ Tutor 11 students per semester on developing strong study habits in Mathematics, Accounting, and Economics✔ Review examinations with students and generate strategies to improve future performance

✔ Audited payments sent to public assistance clients to determine accuracy of each payment✔ Assisted in job search workshops to prepare clients for the job search process including filling out necessary documentation✔ Organized client information and applications, added comments to client profile in database, affixed bar code to each application, and sent follow up information