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 and innovative research to discover systematic anomalies in global macro markets (futures, FX, etc.)
- Perform feature engineering with price-volume, order book and alternative data at intraday to daily horizons in mid frequency trading space
- Perform feature combination and monetization using various modeling techniques
- Manage the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
- Maintain and improve portfolio trading in a production environment
- Contribute to the analysis framework for scalable research
REQUIREMENTS
- Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics
- 2-6 years of signal research experience in macro trading as part of a trading team
- Specialization in swaps, fixed income, or commodities trading a plus.
- Prior professional experience with feature engineering, modeling, or monetization
- Ability to efficiently format and manipulate large, raw data sources
- Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
- Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques
- Collaborative mindset with strong independent research abilities
- Commitment to the highest ethical standards
Skills Required
- Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics
- 2+ years of signal research experience in macro trading as part of a trading team
- Prior professional experience with feature engineering, modeling, or monetization
- Ability to efficiently format and manipulate large, raw data sources
- Demonstrated proficiency in Python, R, or C/C++
- Familiarity with data science toolkits, such as scikit-learn, Pandas
- Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques
- Collaborative mindset with strong independent research abilities
- 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.
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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.
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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.
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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.
Point72 Insights
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.
