Quantitative Researcher - Intraday Trading

Squarepoint Services US LLC seeks a Quantitative Researcher, Investment – Intraday Trading  for its New York, NY location

Duties: On behalf of an investment management firm, 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.

Requirements: Must have a minimum of a Master’s degree or foreign equivalent in any STEM (Science, Technology, Engineering, or Math) field of study and 2 years of experience as a Quantitative Researcher, Quantitative Analyst, Quantitative Trader, Quantitative Strategist, or related position for an investment/asset management organization. Must have at least two (2) years of employment experience with each of the following required skills: working with statistical modelling in day-to-day research of the financial market data to identify and validate patterns in the financial market data; Using Market microstructure to understand order book dynamics, direct the modeling process, and interpret results; Leveraging Python, KDB/Q, and Shell scripting to perform data query, data cleaning, and statistical modeling necessary for the research. Utilizing C++ to implement new business logics and perform system integration. Implementing new functionalities for simulation or live trading. Working with developer IDEs (CLion / Visual Studio Code), and Git version control.Salary / Rate Minimum/yr: $205,000 Salary / Rate Maximum/yr:$280,000. The minimum and maximum salary/rate information above include only base salary or base hourly rate.  It does not include any other type of compensation or benefits that may be available. To apply, visit Careers section of www.squarepoint-capital.com, click on “View Opportunities”, search for applicable job title, and follow application instructions. Squarepoint is an EEO/AA employer.

Squarepoint is a global investment management firm that utilizes a diversified portfolio of systematic and quantitative strategies across financial markets that seeks to achieve high quality, uncorrelated returns for our clients. We have deep expertise in trading, technology and operations and attribute our success to rigorous scientific research. As a technology and data-driven firm, we design and build our own cutting-edge systems, from high performance trading platforms to large scale data analysis and compute farms. With offices around the globe, we emphasize true, global collaboration by aligning our investment, technology and operations teams functionally around the world.