<p>Squarepoint Services US LLC seeks a Quantitative Researcher, Intraday Trading for its New York, New York location.</p> <p>Duties: On behalf of an investment management firm, conduct research and develop quantitative models for intraday commodities trading. Utilize statistical techniques to analyze high-frequency data and identify trading opportunities. Design and implement systematic trading strategies, leveraging programming skills in Python. Continuously refine models based on real-time markets conditions and backtesting results. 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 .Must have a minimum of a Master's degree or foreign equivalent in Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science or Physics and 2 years of experience as a Quantitative Researcher, Quantitative Risk Engineer, 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: Python programming with Pandas, Numpy and Scipy to perform data analysis. Working with trade, position, and market data on futures instruments, including commodities. Developing dashboards with Python and Shell to monitor portfolio and model performance. Running simulations and backtests to analyze the model performance. Must have at least 1 year of experience with the following: Conducting independent research on building forecast models for commodities and communicating results to stakeholders. Applying statistical modeling and machine learning techniques to perform clustering analysis on large financial datasets and extracting features and signals from datasets. Using cloud computing, Linux, and Shell to automate tasks - data ingestion, data outlier detection, feature generation, and daily execution of return forecast processes.</p> <p>Salary / Rate Minimum/yr: $160,000</p> <p>Salary / Rate Maximum/yr: $220,000</p> <p>40 hrs/wk 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. 40 hrs/wk. Squarepoint is an EEO/AA employer.</p>