XIAOYUE (ISABELLA) SUN

217-***-**** • **** N Lake Shore Dr, Chicago, IL 60613 • isabella.xy.sun @gmail.com EDUCATION

UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN Urbana - Champaign, IL Master of Science in Financial Engineering, Jan 2017 FRM – Level I passed, May 2016

UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN Urbana - Champaign, IL Master of Science in Finance, May 2015

NANJING UNIVERSITY OF FINANCE & ECONOMICS Nanjing, China Bachelor of Science, Economics, June 2012

EXPERIENCE

BMO HARRIS BANK Chicago, IL

Practicum Analytics, AML Division August 2016 – December 2016

• Performed Quantitative and qualitative money laundering detection analysis according to Wolfsberg’s Principle upon given big datasets of customer profiles and transaction history utilizing C++, Python, SQL and BigQuery on Google Cloud Platform

• Reduced false positive results via tuning thresholds during the detection and Developed 3 risk rules to construct effective risk rating model with iPython notebook on Google Cloud Datalab

• Utilized visualization techniques to display detection results for each step with iPython notebook

• Created effective customer risk-rating model and back-tested the model using predictive models via logistic regression and random forest classifiers to classify high risk customers based upon data provided PPDAI FINANCIAL INFORMATION TECH Co. Ltd Shanghai, China Quantitative Risk Intern Analyst June 2016 – August 2016

• Participated in stress-testing on the analysis of profitability of several current company’s financial products

• Participated in developing new investment portfolios, listing out candidate ETFs, government bonds and company’s financial loans and products

BANK OF JIANGSU Yancheng, China

Credit Intern Analyst, Credit Department February 2014 – May 2014

• Performed financial analysis on applicant corporates

• Assisted manager to perform due diligence on bank loan by investigating clients account information TIMER CHINA Shanghai, China

Data Analyst, Data Analysis Department June 2012 - January 2014

• Collected raw data for projects, performed data validation, processed raw data for subsequent study and made quantitative and financial analysis upon clients’ requests with statistical and econometrics methods using VBA, R, Eviews and Matlab

• Communicated with and reported to clients during different stages in projects, making adjustments according to feedbacks

• Served as a forum planner for two months and suggested several unique topics for future use PROJECT

COMPARISON BETWEEN BDT AND LMM IN DERIVATIVES PRICING PROJECT Urbana-Champaign, IL Term Structure Project October 2016 – December 2016

• Built and Calibrated both BDT model and LMM to market volatilities using specific techniques, such Rebonato’s Formula and deduction of market caplet implied volatilities.

• Based on the generated short rate tree and long jump forward rate matrix, priced several typical OTC derivative products, namely ATM Caps, ATM European Swaptions, one pre-selected real world product and a Bermudan Swaptions with given terms the selected derivatives.

• By comparing valuation results via 2 models, we had a deeper qualitative and quantitative understanding of these 2 models, especially about the built-in features, algorithm implementation, financial derivative decomposition methods and appropriate application fields.

STOCK RETURN PREDICTION MODEL VALIDATION PROJECT Urbana-Champaign, IL Risk Management Project February 2016 – May 2016

• Processed 8-year daily trading data eight kinds of options on 3295 stocks with R

• Validated the given cross-sectional regression model theory with real world data

• Developed trading strategy using prediction performance of stocks and back-tested profitability of initial trading strategy TRADES AND SUBSEQUENT EFFECTS PROJECT Urbana-Champaign, IL High-Frequency Trading Market Project February 2016 – June 2016

• Processed one-day high-frequency raw trading data and order book of E-mini with time-interval as one millisecond, with around 500,000 lines of data

• Adopted statistics data analysis methodology, mathematical deduction, R and C++ to slice data, plot out important trend and adjusted reference paper theories and models

• Derived an effective model for simulation of E-mini price and compared the result with Hawkes Process SKILLS

Programming: Python, R, SQL, C++, Matlab, Eviews, VBA, Bloomerberg Terminal, Microsoft Office Suite, Google Analytics Professional: Data Analysis, Risk Management, Machine Learning ACTIVITIES & LEADERSHIP

Simultaneous Interpreter, China Executive Leadership Program, UIUC, July 2014 - Now President, Debate &Lecture Association, NJUE, September 2009 - June 2010 Team Leader, University Debate Team, NJUE, September 2009 - June 2010 Volunteer, Yancheng Welfare Center for Children, Government Yancheng, June 2008 - April 2014 Interpreter/Subtitle Maker, Online Subtitle group, March 2009 - October 2012

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