Data Analyst Python

Peiran Li

**** ***** **. *** *******, CA ***** • ***********@*****.*** • 213-***-****

EDUCATION

University of Southern California, Los Angeles, CA Aug 2018 - May 2020

• Master of Science in Financial Engineering (STEM) GPA:3.4/4.0 Sichuan University, Chengdu, China Sept 2012 -July 2016

• Bachelors of Science in Financial Management and Polymer Materials Processing Engineering SKILLS

• Python, SQL, R, MATLAB, Financial Modeling • Languages: Mandarin (Native), English (Fluent)

• Machine Learning, Reinforcement Learning, Convex Optimization, Data Mining, Time-Series Analysis A/B Testing PROFESSIONAL EXPERIENCE

Financial Data Analyst, Magnus Investment Partners, Malibu, California, United States May 2020 – Present

• Scanned the Top 2000 market cap stocks of the US equity market and conducted the quantitative analysis with Python (Pandas, Numpy, etc.) for the stocks affected by the pandemic.

• Conducted momentum strategy to generate an upward stock portfolio benefits from the isolation of the pandemic with a 14.34% return in 20 days.

• Implemented data analysis on the luxury car collector clubs project of this real estate private equity investment firm and built valuation models using discounted cash flow (DCF) analysis and comparable company analysis.

• Cleaned sold and listed house data from Silver Laker area and generated house pricing and renovation cost model with Linear Regression with 96.31% accuracy extending to another 30 locations. Business Data Analyst, Shangxue Counseling Service, Hohhot, Inner Mongolia, China April 2018 – Aug 2019

• Started a consulting business for student college applications through cleaned previous 10-year application data.

• Deleted the outliers and filtered the students into a list of 3 schools based on ranking and preference.

• Conducted customized counseling for 20 students in 10 days before the national online application system closed. Business Analyst, Yili Industrial Group Co., Ltd. Hohhot, Inner Mongolia, China May 2018 - July 2018

• Created logistics tables, inserted orders using SQL and analyzed distributor performance and sales promotions based on expired product ratio metrics I helped design.

• Conducted time-series analysis to forecast sales revenues and temporary promoters, realizing 3% growth. PROJECTS

Constructed Conservative Formula Portfolios Jan 2020 – current

• Cleaned SAS dataset utilizing Python to create a portfolio of 100 stocks on NYSE with low return volatility, high net payout yield, and strong price momentum and rebalanced this portfolio quarterly.

• Generated an annual return of 15.1% and reduced downside risk, backtesting from 1929. Reinforcement Learning in Optimal Hedging Sept 2019 - Dec 2019

• Constructed the Black-Scholes model with Python to price an option as a discrete-time replication of stock and bond. QLBS Model solved the Bellman equation by Q-learning method, only relying on price data.

• Generated different trajectories for the assets and implemented Monte Carlo simulation to test model and Q- learning to predict the outcomes, automatically optimizing the decision to gain the highest stock return. A Trading Algorithm for Enhanced Alpha Strategy Sept 2019 – Oct 2019

• Filtered stock price pipeline with financial ratios and NLP sentimental analysis scores to enhance the combined Alpha. Conducted linear programming to optimize return under the strategy constraints and generated trading signals.

• Outrun the S&P 500 by 4.5% with a more smoothed return through backtesting. Fama-French Factors Regression Aug 2019 - Sep 2019

• Conducted a three-factor regression using Python with Panda and Numpy for each S&P 500 stocks for every quarter.

• Extracted time-series averages for each coefficient and conducted hypothesis testing.

• The t-stat of BM, OP and size factor is not significant separately, but the enhanced factor is significant.

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