SUMMARY:
Data analyst with 4+ years experience developing financial trading models and assessing fund performance. Academic background in mathematics with a focus in actuarial science, statistics and probabilities. Experience working in high pressure environments with nontraditional hours, both team - oriented and independent positions.
SKILL:
R, Python, VBA, SQL/MySQL
Advanced Microsoft Excel
Data modelling/data mining
Data visualization/reporting
Trade execution (discretionary and algorithmic)
PROFESSIONAL EXPERIENCE:
Quant Analyst/Programmer
Confidential, Chicago, IL
Responsibilities:
- Repair and reformatting of poorly constructed Excel model (equity trading)
- FX and futures model creation and optimization
- Cryptocurrency trade analysis and accounting
Quant Programmer
Confidential, Chicago, IL
Responsibilities:
- Created, validated and optimized FX trading models
- Programmed automation of trading strategy and managed its implementation
- Monitored automated system running 24 hours/day on a VPN
- Worked with principal investor to further develop existing strategy
Manager of Summer Internship Program (Intern)
Confidential, Chicago, IL
Responsibilities:
- Managed a 6-person team in 5 departments operating enhanced algorithmic FX trading fund
- Ran morning discretionary trading sessions
- Taught risk management and algo skills to intern group; maintained models during initial intern training period
- Managed procedural documentation and compliance; oversaw presentation of results to board of directors
Intern
Confidential, Chicago, IL
Responsibilities:
- Project leader on coded automation of a trading model and accompanying documentation
- Contributed to development and presentation of intensive 4-day Excel/algo training program
- Developed 5-minute FX model; assisted with development of crude oil futures model
- Trader on 4-hour EUR/USD model
Algorithmic Modeling Intern
Confidential, Chicago, IL
Responsibilities:
- Developed, validated and optimized algos trading S&P e-minis, gold and crude oil
- Produced presentations to explain dynamics of model and P/L to investors
