Quantitative Risk Management Analyst
Location: Chicago or New York
Daily responsibilities include code release testing, historical data validation, margin and stress testing model validation, and portfolio back-testing. The candidate must have the ability to efficiently, effectively, and independently conduct research, analyze problems, formulate and implement solutions, and produce high quality results on time.
Skills / Software Requirements:
- Strong quantitative and analytical background.
- Excellent programming, communication, and documentation skills.
- Knowledge of financial markets.
- Knowledge in advanced quantitative risk modeling and knowledge of statistical models in risk management preferred.
- Knowledge in advanced derivatives modeling and knowledge of volatility models preferred.
- Experience with programming languages such as C++/C#, R, VBA, and SQL is also required.
- Preference will be given to candidates who can demonstrate the best practices in developing risk models like Historical VaR, Monte Carlo VaR, Multi-Factor Risk Models, Stressed VaR, Liquidity Risk models, etc.
- Bachelor or Masters in Computer Science, Financial Engineering, Financial Mathematics, Mathematics, Physics, or a related discipline.