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    Quantitative Researcher - Chicago, United States - Durlston Partners

    Durlston Partners
    Durlston Partners Chicago, United States

    4 weeks ago

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    Description
    Quant Researcher
    • Options Market Making $600kHiring an experienced Quant Researcher to develop quantitative models for a high performance options market making desk.
    Work closely with the technology teams to ensure that trading models and algorithms are seamlessly integrated into the trading infrastructure, with a focus on low-latency execution.


    Key Responsibilities:

    Quantitative Model Development:
    Develop and refine quantitative models for models for pricing, volatility forecasting, and the identification of short-term arbitrage opportunities

    Market Data Analysis:
    Deep dive into market data and identify trading opportunities.

    Leverage your expertise in statistical analysis to parse through vast datasets, applying machine learning algorithms where appropriate to enhance decision-making processes.


    Strategy Optimization:
    Optimize risk management and execution efficiency

    Back-Testing and Performance Analysis:
    Conduct rigorous back-testing of strategies, and evaluate potential profitability and risk. Utilize post-trade analysis to iterate and refine strategies, ensuring continuous improvement and adaptation to market conditions.


    Required Skills and Qualifications:
    Expertise in options trading and market making, with a strong track record of developing successful quantitative strategies.
    A deep understanding of option pricing models, volatility surface dynamics, and the mechanics of options markets. Familiarity with the regulatory environment and compliance standards affecting options trading.

    Outstanding quantitative and analytical capabilities, with a proven ability to tackle complex data analysis challenges and apply innovative problem-solving techniques.

    Exceptional skills in Python & C++ programming.


    Advanced Quantitative Degree:
    A Ph.
    D. or Master's degree in a quantitative field such as Financial Engineering, Mathematics, Statistics, Physics, or a closely related discipline.


    Desired:
    Experience in a high-frequency trading environment is highly valued.
    Experience with database management and familiarity with machine learning frameworks is preferred.#J-18808-Ljbffr
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