Job Description

Seeking an experienced Options Quant developer to lead the design, architecture, and implementation of an automated options trading system. The position involves working closely with a small, experienced team of traders, quants, and seasoned software engineers.

Responsibilities will include:

• Leading various options quantitative initiatives.
• Focusing on areas such as volatility pricing.
• Managing cross-product risk.
• Collaborating closely with traders to develop and enhance existing processes and systems.
• Applying observation skills and modern statistical methods to identify and build predictive models.
• Researching and implementing new volatility trading strategies and identifying volatility signals.
• Analyzing existing strategies to identify areas for potential improvements.
• Developing risk models and frameworks specifically for managing cross-product portfolio risks within the volatility space.

Required Qualifications and Experience:

To be considered for this role, candidates must meet several key requirements:

• Demonstrated practical experience in options pricing, within an automated or high-frequency trading environment, ideally in a market making context.
• Candidates must possess a solid understanding of risk management and valuation models.
• Practical experience is essential in specific areas including:
• Modeling implied and realized volatility.
• Managing and calibrating volatility risk.
• Identifying and utilizing volatility trading signals.
• Modeling and assessing event risk.
• Understanding and implementing order placement logic.
• Performing PnL (Profit and Loss) analysis.
• Understanding microstructure effects.
• Strong programming skills are mandatory, specifically in C++ and Python.
• Candidates must demonstrate exceptional quantitative, mathematical, and problem-solving skills.
• Great communication skills and the ability to collaborate effectively with peers are necessary.
• An advanced degree is required, preferably a PhD, in a quantitative field such as Science, Math, Engineering, or another related quantitative discipline.

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