Quantitative Researcher - Volatility
About The Position
Squarepoint Services US LLC seeks a Quantitative Researcher for its Volatility Team in New York, New York. This role involves formulating mathematical and simulation models for investment strategies, enhancing trading through computerized algorithms, and implementing these models. The researcher will utilize comprehensive knowledge of mathematical models, statistical techniques (including regression analysis, machine learning, and statistical inference), and financial and computer skills to improve investment strategies in equities and other asset classes. Key responsibilities include producing sophisticated analyses of statistical effects, assessing their robustness, developing new quantitative strategies, and performing validation and testing of trading simulations and applications. The role also requires building applications using Shell and Python for data processing automation, analyzing strategy behavior with KDB/Q and Python, and tracking market history with Excel/VBA and KDB tools to evaluate profit potentials and risk margins. Additionally, the position involves managing live trading automatons, monitoring associated risks, leveraging asset-class-specific experience to find market patterns and optimize execution costs, and utilizing knowledge of market structure and statistical arbitrage to enhance and develop trading strategies. The Quantitative Researcher will also assist senior researchers in developing and maintaining automated trading models and pilot research projects across teams and regions to create new mathematical models and analytical tools for investment decision-making.
Requirements
- Minimum of a Master’s degree or foreign equivalent in Financial Engineering / Financial Mathematics or related.
- 1 year of experience as a Quantitative Researcher, Quantitative Trader, or related position for a hedge fund or market maker.
- At least one (1) years of employment experience with utilizing options knowledge to perform asset specific research and engage in real trading.
- At least one (1) years of employment experience with analyzing, optimizing, and blending different styles of signals that predict various targets in options market.
- At least one (1) years of employment experience with conducting option portfolio construction based on mathematical optimization problems.
- At least one (1) years of employment experience with simulating different systematic trade ideas and evaluating backtest performance.
- At least one (1) years of employment experience with developing monitoring reports for live strategies and performing risk management.
- At least one (1) years of employment experience with programming in kdb+/q and python for data analysis and strategy development.
Responsibilities
- Formulate mathematical and simulation models of investment strategies, relating constants and variables, restrictions, alternatives, conflicting objectives, and numerical parameters for the enhancement of trading through computerized algorithms, as well as implementation of models.
- Utilize comprehensive knowledge of mathematical models and technologies, statistical techniques including regression analysis, machine learning, and statistical inference, and financial and computer skills in order to enhance investment strategies based on equities or other asset classes.
- Produce and implement sophisticated analyses describing new statistical effects, assessing robustness of effects, and developing new quantitative strategies making use of such effects.
- Perform validation and testing of both trading simulations and critical trading applications.
- Build applications utilizing Shell and Python to automate daily data dependency processing for trading strategies.
- Utilize KDB/Q and Python to analyze existing strategy behavior and propose and implement improvements.
- Utilize Excel/VBA mathematical models and KDB analysis tools to track market history of specific asset classes to evaluate future profit potentials and risk margins.
- Manage live trading automatons and perform continuous monitoring of risk related to live trading automatons.
- Leverage on asset-class-specific experience to find new patterns in market data and explore new methods to optimize execution costs.
- Utilize extensive knowledge of market structure and statistical arbitrage to improve on existing trading strategies and develop new trading strategies.
- Assist team’s senior quantitative researcher’s efforts in building, validating, releasing, and maintaining highly complex automated trading models.
- Pilot research projects spanning multiple teams across multiple regions to develop new mathematical models and analytical tools for critical investment decision making.
- Utilize options knowledge to perform asset specific research and engage in real trading.
- Analyze, optimize, and blend different styles of signals that predict various targets in options market.
- Conduct option portfolio construction based on mathematical optimization problems.
- Simulate different systematic trade ideas and evaluate backtest performance.
- Develop monitoring reports for live strategies and perform risk management.
- Program in kdb+/q and python for data analysis and strategy development.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
