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Quantitative Researcher

Point72
Dubai, UAE
Full-time
Mid-Senior
Onsite
Discovered 2 weeks ago
Quantitative finance researchStatistical modelingPredictive modelingLarge-scale data analysisBacktestingPerformance monitoring
Free

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Quantitative finance researchStatistical modelingPredictive modeling
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About Cubist

Cubist Systematic Strategies is an affiliate of Point72 that deploys systematic, computer-driven trading strategies.

The strategies cover liquid asset classes including equities, futures, and foreign exchange.

The research effort focuses on market anomalies using broad publicly available data sources.

Job Description

Researchers independently conduct quantitative finance research focused on statistical and predictive models.

Successful researchers manage methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring.

Researchers may join from similar firms, related fields, or academia and receive hands-on guidance from experienced portfolio managers and researchers.

Research Scope

  • Conduct independent quantitative research across the full research process.
  • Analyze large data sets and investigate quantitative finance questions.
  • Develop, test, prototype, backtest, and monitor quantitative research ideas.

Desirable Candidates

  • MS or PhD candidates in finance, computer science, mathematics, physics, or another quantitative discipline are desirable.
  • Three to seven years of alpha-driven quantitative research experience across equities, futures, fixed income, credit, or foreign exchange is desirable.
  • Strong analytical and quantitative skills are desirable.
  • Independent research experience using large data sets is desirable.
  • Programming in C++, Java, C#, MATLAB, R, Python, or Perl is desirable.
  • Detail orientation and ownership of work are desirable.
  • The ability to work independently and within a small team is desirable.

Candidate Profile

The team values strong technical skills, problem-solving ability, curiosity about financial markets and human behavior, and exceptional personal achievements.

Relevant engineering or data projects from outside school or coursework may be highlighted in an application.

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