Quantitative Researcher

Point72 • Bachelor's Degree • C++ • Python • 10 days ago
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Salary
≈ $108k – $226k per year (Estimated)
Location
In office (New York)
Seniority
Middle · 3+ years exp
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Point72

Point72 is a global, multi-strategy hedge fund manager founded by Steven A. Cohen that invests across discretionary long/short equity, systematic, and macro strategies. The firm relies heavily on fundamental research, quantitative models, and advanced data analytics to allocate capital across international financial markets. Headquartered in Stamford, Connecticut, it also manages Point72 Ventures, an early-stage venture capital arm focused on investing in emerging technology startups.
point72.com • HQ: Stamford, United States • Venture Capital • Financial Services • Asset Management • 501-1000 employees • Est. 2014

ABOUT CUBIST

Cubist Systematic Strategies is one of the world’s premier investment firms. The firm deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

RESPONSIBILITIES

  • Perform rigorous applied research to discover systematic anomalies in equities markets
  • Present actionable trading ideas and enhance existing strategies
  • Identify short term opportunities in the high frequency/intraday space
  • Participate in end-to-end development (i.e. data orchestration, alpha idea generation, simulation, strategy implementation, and performance evaluation)
  • Contribute towards the team’s research tooling and its efficiency
  • Help establish a collaborative mindset and shared ownership

REQUIREMENTS

  • Bachelor’s degree or higher in mathematics, statistics, computer science, or similar quantitative discipline
  • 3+ years of work experience in systematic alpha research in equities using high frequency/intraday data
  • Fluency in data science practices, e.g., feature engineering, signal combining
  • Technically comfortable handling large datasets
  • Comfortable coding in both C++ and Python in a Linux environment
  • Exposure working with cloud computing platforms such as AWS
  • Highly motivated and willing to take ownership of his/her work
  • Collaborative mindset with strong independent research ability
  • Commitment to the highest ethical standards
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