Data Analyst (intern) Resume
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TECHNICAL SKILLS:
Software: Python, R, SAS, MATLAB, SQL Server, C/C++, Bloomberg, VBA, MS Office
Language: Fluent in English, proficient in Mandarin
PROFESSIONAL EXPERIENCE:
Confidential
Data Analyst (Intern)
Responsibilities:
- Extracted, compiled and tracked data with Excel and SQL Server
- Analyzed data to generate reports
- Worked with other team members to complete projects and achieve project deadlines
Confidential
Intern
Responsibilities:
- Examined dataset, forecasted premium according to customer category with SAS
- Produced relevant results with plots and generated reports
- Presented related initiatives and results with Microsoft Power Points
Confidential
Responsibilities:
- Applied discrete time binomial CRR model to pricing European style vanilla options in MATLAB
- Tested the model with underlying PG, calibrated the model with Hull White Theorem, plotted the graphs for theoretical and market prices
- The trends for call and put options between simulation and real market prices are almost the same and the models are feasible
Confidential
Responsibilities:
- Collected stock market data from Interactive Brokers Paper Trading account, applied Black - Scholes-Merton model, and stochastic volatility model to hedge the options by using MATLAB
- Verified model with single options, calibrated the model to market data
- Rebalanced the portfolio, kept track of trades, relative errors are between 0%~8%
Confidential
Responsibilities:
- Calculated Portfolio duration, convexity, and yield based on T-Bonds and T-bills
- Created a Credit Spread trade using Treasury bills and Eurodollar futures
- Constructed steepener, flattener, and butterfly trades with T-bills
- Calculated the TED Spread value and P&L of the Portfolio and trades
Confidential
Responsibilities:
- Used MATLAB code to generate correlated uniform variables
- Built visualized models in Anylogic to simulate four different scenarios using Monte Carlo theory
- Compared the results,created strategies to increase the efficiency and profit of the restaurant
Confidential
Responsibilities:
- Compiled Python code for Random Forest theory
- Tested accuracy(85.71%) with ‘Wine’ dataset
- Compared the accuracy with provided R package functions in R(91.67%)