Data Scientist

J U N J I E S U N

** *********** ******** ***** ***. 1804, Jersey City, NJ 07302

917-***-**** ******@********.***

EDUCATION

Columbia University

M.S. in Financial Engineering, GPA: 3.93/4.0

New York, NY

Aug 2018 – Dec 2019

• Coursework: Financial Engineering, Optimization, Stochastic Models, Applications Programming, Monte Carlo Simulation, Statistical Analysis and Time Series, Implied Volatility Smile, Algorithmic Trading, Computational Methods in Finance, Structured and Hybrid Products Tsinghua University

B.E. in Automation, GPA: 87/100

Beijing, CN

Aug 2014 – Jul 2018

• Coursework: C/C++ Programming, Data Structure, Computer Principles and Applications, Signals and System, Automatic Control Theory, Pattern Recognition, Database System, Numerical Analysis and Algorithms KTH Royal Institute of Technology

Exchange Student

Stockholm, SE

Aug 2016 – Jan 2017

EXPERIENCE

Moloco, Inc.

Data Scientist, Operations Data Science

New York, NY

May 2020 – Present

• Managed digital marketing campaigns and conducted deep-dive analysis to improve performance.

• Built data pipelines for data transformation and reporting with Google BigQuery as data warehouse and Jenkins.

• Created Looker dashboards for visualization used by internal and external clients.

• Analyzed performance of campaigns launched on new platform to support decision to increase lowest starting budget.

• Designed and analyzed experiments of spending control on click-through install ratio and provided recommendations. Trinnacle Capital Management, LLC

Intern, Quantitative Analyst

New York, NY

Sep 2019 – Dec 2019

• Fixed the trade log management system and developed functions of calculating historical positions and P&L.

• Developed parallel programs for retailers’ footfall data analysis and trading signal research on Amazon Web Services.

• Built a Python program to parse freight futures market quotes from brokers’ messages and manage the database. Deutsche Bank Securities Inc.

Summer Analyst, Fixed Income & Currencies Quant

New York, NY

Jun 2019 – Aug 2019

• Retrieved Eurodollar options quotes data through Bloomberg Excel Add-in with a VBA Macro.

• Tested for cointegration between at-the-money implied volatility of swaptions and Eurodollar options.

• Proposed a method to mark the fair value of at-the-money swaption’s implied volatility based on linear regression.

• Applied Kalman filters on intraday Casado prices and detected changes of market state.

• Performed likelihood ratio test for mean-reversion in intraday Casado prices. Wacai Financial Information Service Co., Ltd.

Summer Intern, Data & Risk Management

Shanghai, CN

Jun 2017 – Aug 2017

• Created stored procedures in MySQL Server to extract features of more than 20,000 loan applicants.

• Built credit scorecard model based on logistic regression for prediction of personal loan default risk.

• Developed a neural network class in the modeling platform using TensorFlow, of which K-S statistics beat benchmark. PROJECTS

SSVI Parametrization of Implied Volatility Surfaces Oct 2019 – Dec 2019

• Calibrated surface stochastic volatility inspired (SSVI) model to observed stock option prices and checked absence of static arbitrage in the calibrated surfaces; average error was smaller than 1% and 0.2% for short and long maturities. Mid-Price Price Movement Factor in Intraday Trading Execution Strategy Apr 2019 – May 2019

• Applied machine learning models to predict mid-price movement with limit order book data and generated a factor for intraday factor-based trading execution strategy from liquidity taker’s perspective. Applications Programming for Financial Engineering Sep 2018 – Dec 2018

• Implemented quadratic programming for mean-variance portfolio optimization with constraints in Python and C++.

• Built a multithreaded C++ program that optimized trade execution with market impact using dynamic programming. Application of Graph Embedding on Single-Cell Clustering Dec 2017 – Jun 2018

• Constructed graphs of single cells from gene expression data and developed a graph embedding algorithm based on Skip-gram model in NLP and random walk sampling with transition probabilities; built the workflow with Python.

• Applied clustering algorithms to evaluate the performance of cell type identification, outperforming the benchmarks. SKILLS & OTHERS

Programming: C/C++, C#, MATLAB, Python (NumPy, pandas, scikit-learn), R, Spark, SQL, VBA, Git, LaTeX Online Education: Machine Learning by Stanford University on Coursera. Certificate earned in 2016. Awards: 2nd Prize in China University Mathematics Competition in Beijing (for non-math majors), Nov 2015 2nd Prize in National High School Mathematics Competition in Shanghai, Oct 2013

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