Quantitative Analyst for Trading Systems
Budget: $250 – $750 USD
## Professional Summary
Quantitative analyst with 3+ years experience in algorithmic trading. Proficient in Python with expertise in independently building end-to-end quantitative trading systems. Specialized in cryptocurrency and traditional financial markets.
## Technical Skills
- **Languages:** Python (Pandas, NumPy, scikit-learn, PyTorch)
- **Quantitative:** Statistical arbitrage, Mean reversion, Factor modeling, Risk management
- **Trading:** Crypto exchanges (Binance, OKX), Backtesting, Strategy development
## Work Experience
**Quantitative Developer** | Shanghai Quantitative Capital | 2021.09 - Present
- Independently developed cryptocurrency trading system managing $3M AUM
- Designed 15+ trading strategies with live performance of 18-35% annual returns
- Built multi-factor stock selection model achieving 12.8% annualized alpha
- Developed high-frequency backtesting framework (10M data points/minute)
## Projects
**Independent Trading System** | Personal Project
- Real-time data from 8+ exchanges with modular strategy framework
- 3-year live track record: 24.7% CAGR, Sharpe 1.8, Max DD 12.3%
- Automated risk management and deployment pipeline
## Education
**MSc in Financial Engineering** | Shanghai Jiao Tong University | 2018-2020
Quantitative analyst with 3+ years experience in algorithmic trading. Proficient in Python with expertise in independently building end-to-end quantitative trading systems. Specialized in cryptocurrency and traditional financial markets.
## Technical Skills
- **Languages:** Python (Pandas, NumPy, scikit-learn, PyTorch)
- **Quantitative:** Statistical arbitrage, Mean reversion, Factor modeling, Risk management
- **Trading:** Crypto exchanges (Binance, OKX), Backtesting, Strategy development
## Work Experience
**Quantitative Developer** | Shanghai Quantitative Capital | 2021.09 - Present
- Independently developed cryptocurrency trading system managing $3M AUM
- Designed 15+ trading strategies with live performance of 18-35% annual returns
- Built multi-factor stock selection model achieving 12.8% annualized alpha
- Developed high-frequency backtesting framework (10M data points/minute)
## Projects
**Independent Trading System** | Personal Project
- Real-time data from 8+ exchanges with modular strategy framework
- 3-year live track record: 24.7% CAGR, Sharpe 1.8, Max DD 12.3%
- Automated risk management and deployment pipeline
## Education
**MSc in Financial Engineering** | Shanghai Jiao Tong University | 2018-2020
Related categories:
Python
Statistics
R Programming Language
Statistical Analysis
Data Science
NumPy
Backtesting
Pandas
Cryptocurrency