- Test and validate code releases for all client/platform releases (regression/UAT-style testing)
- Validate historical market data (completeness, accuracy, outliers, breaks)
- Validate margin & stress testing model outputs and investigate unexpected movements
- Run portfolio back-testing to evaluate model performance vs. historical outcomes
- Document findings clearly and communicate results to quants, developers, and stakeholders
- Independently research issues, diagnose root cause (data vs. code vs. config), and drive solutions
- 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 are preferred.
- Knowledge of advanced derivatives modeling and knowledge of volatility models preferred. xhuatnn
- Experience with programming languages, Python, 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.
- Master's in Computer Science, Financial Engineering, Financial Mathematics, Mathematics, Physics, or related discipline
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Quantitative Analyst - New York - Secure RPO
1 week ago
Description
Job Summary:
If you think you are the right match for the following opportunity, apply after reading the complete description.Join a Risk Management team in a consulting contract role, where accuracy matters, and results are measurable. You'll partner closely with Quant Risk and IT to test and validate margin and stress models across multiple asset classes, helping ensure the firm's clearing initiatives run smoothly, safely, and reliably.
What you'll do (day to day):
Skills / Software Requirements:
Education:
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