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    Quantitative Analyst/Software Developer - New York, United States - Point72

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    Description

    About Our Team

    KEPL is an elite team at Cubist Systematic Strategies trading medium-frequency statistical arbitrage strategies with high Sharpe. We are actively expanding to new markets and assets classes. We have a collaborative culture, and we embrace cutting edge technologies to facilitate innovative research. The team is led by a few industry experts from top tier trading and tech firms, including D.E. Shaw, Citadel, Two Sigma, Facebook AI Lab, etc.

    Role:

    We are looking for a hybrid role of quantitative research analyst and software developer to join our fast-growing team and contribute to multiple new initiatives that aim to expand our business. The candidate should have a passion in technology to provide optimal solution to research and trading. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative research and trading. The candidate will play an essential role for the team's successful expansion. The candidate will also collaborate with researchers to innovate research tools which will take our research and trading capability to the next level.

    Responsibilities:

  • Develop, maintain, and improve the production trading system. Conduct research to further enhance team's monetization.
  • Build technologies that bolster research & trading productivity.
  • Expand the system to new markets and asset classes.
  • Requirements

  • Master/PhD degree in math, physics, computer science, engineering, or other related discipline.
  • 1-3 years of professional experience in software development or quantitative research.
  • Strong combination of quantitative skills and programming skills.
  • Proficiency in Python 3 and either C++ or Java.
  • Familiarity with the Linux environment
  • The annual base salary range for this role is $200,000-$300,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

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