Quantitative Researcher, ADRs, ETFs and Futures (AEF)

Posted 3 Days Ago
Be an Early Applicant
New York, NY
1-3 Years Experience
Financial Services
The Role
The Quantitative Researcher will develop mathematical models and simulations to enhance trading strategies using advanced statistical techniques and machine learning. Responsibilities include analyzing asset behavior, implementing trading applications, managing automated trading systems, and conducting research to optimize execution costs.
Summary Generated by Built In

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.

Squarepoint Services US LLC seeks a/an Quantitative Researcher for its New York, New York 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, convex optimization, 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. Analyze lead/lag effects between assets. 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. Reconciling ETF  NAVs and compositions. Exercising creation and redemption between ETFs and stock baskets.

Requirements: Must have a minimum of a Master’s degree or foreign equivalent in Finance or any STEM (Science, Technology, Engineering, or Math) field of study and 1 year of experience as a Quantitative Researcher, Analyst, or related position for an investment/asset management organization developing machine learning models to analyze market data, exploit market patterns and explore trading opportunities. Must have experience with each of the following required skills: Working with Q, Kdb and Python programming languages. Utilizing Linear and non-linear optimization to make portfolio construction decisions with real-life constraints and applying techniques to improve trading strategies and minimize costs. Using machine learning algorithms to help alpha-generating and trading strategies research. Applying general equilibrium theories to support the decision-making process of investment and using asset pricing models to access the risk associated with different asset classes. Analyzing the return risk profile of fixed income securities in investment portfolios and identifying risk attributes to support strategy development. Developing statistical models to exploit the relationship between independent and dependent variables. Salary / Rate Minimum/yr: $150,000. Salary / Rate Maximum/yr: $185,000. 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.



Top Skills

Kdb/Q
Python
The Company
HQ: New York, New York
1,267 Employees
On-site Workplace
Year Founded: 2014

What We Do

Squarepoint Capital is a leading global investment management firm that develops quantitative investment strategies to achieve high quality returns for our clients. We are a data and technology driven firm who specialize in developing automated trading systems that execute across global financial markets.

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