Geneva Trading USA, LLC seeks a Quantitative Trader at its facility located at 190 S Lasalle St, Suite 1800, Chicago, IL 60603.
JOB DESCRIPTION :
Monitor and execute algorithmic trading strategies in live markets to capitalize on trading opportunities. Actively manage risk to maximize profits in accordance with all company’s risk procedures. Conduct research of past trading performance to improve revenue capture, risk management, and market coverage. Propose and deploy new trading models by analysis of financial time series data with fundamental statistical theories. Take initiative with research, identification, and implementation of profitable trading algorithms. Collaborate closely with quantitative analysts and contribute new analysis material to team’s knowledge database. Use systematic and analytical skills to anticipate problems and proactively formulate solutions. Monitor and troubleshoot proprietary software and trading infrastructure. Propose, research, back test, and optimize new features for proprietary trading system. Collaborate with other Traders, Quants, and Developers to improve proprietary trading system performance. Hybrid (2 days per week telecommuting permitted).
_REQUIREMENTS: _
- This position requires a Master’s degree, or foreign equivalent, in Financial Engineering, Financial Mathematics, or a related field.
- 2 years of experience as a Quantitative Trader, Quantitative Analyst, or related occupation in a trading firm or hedge fund.
- Applicant must have employment experience with:
- Designing, developing, and modifying trading strategies, using scientific analysis and mathematical models to predict and measure outcome.
- Analyzing definitions and fundamentals of financial products and their derivatives to fully understand and develop pricing models.
- Performing financial strategy design, analysis, and parameter optimization to maximize strategy performance using calculus, linear algebra, probability, statistics, and stochastic process.
- Designing and implementing multivariate data analysis of financial data set to back test trading strategies.
- Conducting analysis of market datasets by utilizing market theories to understand details of exchange and product specific market data.
- Utilizing game theory, statistical analysis, and risk-based optimization to maximize expected returns.
- Writing and implementing statistical ideas in Python and R to systemize market analysis and optimize trading strategies.
- Knowledge of data science techniques to provide historical/real time analytics on observed market patterns and predictive time series modelling using Machine Learning methods such as regression and classification techniques.
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