Quantitative Researcher, Volatility - Medium-Frequency

New York, NY, United Statesvia Squarepoint Capital CareersPosted Oct 9, 2026
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Technical skills

PythonData analysis

About this role

Squarepoint Services US LLC seeks a Quantitative Researcher (Volatility

  • Medium- Frequency) for its New York, New York location.

Duties: Construct, analyze, and manage single stock portfolios. Conduct equity execution research to optimize trading strategies. Perform market impact analysis to minimize trading costs. Research and enhance monetization of alpha signals. (Monitor portfolio exposures, risk metrics, factor sensitivities, and performance attribution daily to support risk management. Produce research reports and quantitative insights on portfolio performance, trading costs, signal effectiveness)

Requirements

Must have a minimum of a Master’s degree or foreign equivalent in Financial Engineering or related field of study and 1 year of experience as a Quantitative Researcher or related position for an investment/asset management or financial market research organization. Must have at least one (1) year of employment experience with each of the following required

skills

Quantitative modeling and statistical analysis;Multi‑asset portfolio construction and risk management; Algorithmic trading and execution optimization; Market‑impact analysis; Alpha research, signal development, and validation; Programming using Python for data analysis and strategy development Salary / Rate Minimum/yr: $160,000 Salary / Rate Maximum/yr: $185,.000 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. Squarepoint is an EEO/AA employer.

Before you apply

  • 1Which parts of your CV prove experience with Python and Data analysis?
  • 2Which recent work examples would make your application stronger for this role?
  • 3What details from the original source listing should you confirm before applying?

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