Quantitative Researcher

Point72; New York (NY); On-site; USD 175,000 - 200,000; Full time

Job summary

Cubist, an affiliate of Point72, is seeking a rigorous researcher to discover systematic anomalies in equities and present actionable trading ideas. You will identify short-term opportunities in the high-frequency/intraday space and participate in end-to-end development from data orchestration to strategy evaluation.

The role emphasizes data-driven research, collaboration, and ownership of projects, with a focus on scalable research tooling and ethical standards within a dynamic, quantitative

Qualifications

• 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.

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

Skills

Data science practices

Independent research

Ownership mindset

Collaborative mindset

Education

Bachelor’s degree or higher in quantitative field

Tools

C++

Python

Linux

AWS

Job description

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, 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.

Role/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

The annual base salary range for this role is $175,000-$200,000 (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.