Quantitative Researcher

Reposted Yesterday
Chicago, IL, USA
In-Office
Mid level
Financial Services
The Role
Conduct research to identify market anomalies, generate trading ideas, and develop systematic strategies focusing on high frequency/intraday opportunities.
Summary Generated by Built In

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

Skills Required

  • 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 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

Point72 Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Point72 and has not been reviewed or approved by Point72.

  • Healthcare Strength Healthcare coverage is described as exceptional with comprehensive options and low out-of-pocket costs. Medical, dental, and vision are characterized as fully covered or no-premium for U.S. employees.
  • Retirement Support The 401(k) program features a generous employer match and access to after-tax contributions with in-plan Roth conversions. Value accrues through a multi-year vesting schedule that rewards tenure.
  • Parental & Family Support Parental and family leave is highlighted as generous and has strengthened over time. Clear primary and secondary caregiver policies are in place and seen as competitive.

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The Company
HQ: Stamford, CT
1,691 Employees
Year Founded: 2014

What We Do

Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here.

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