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Quantitative Researcher - Macro

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Experienced Professionals

New York

Systematic Investing


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.


Senior quantitative researcher to help build out a new systematic macro (futures, FX, and vol) business. Core focus will be working on mid-frequency alpha strategies.

Job Description

  • Develop systematic trading models across FX, commodities, fixed income, and equity markets
  • Alpha idea generation, backtesting, and implementation
  • Assist in building, maintenance, and continual improvement of production and trading environments
  • Evaluate new datasets for alpha potential
  • Improve existing strategies and portfolio optimization
  • Execution monitoring
  • Be a core contributor to growing the investment process and research infrastructure of the team

Desirable Candidates

  • Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus
  • 3-5 years of experience in quantitative trading, ideally in FX or futures
  • Experience with alpha research, portfolio construction and optimization
  • Experience building statistical/technical, fundamental, and data driven signals
  • Experience synthesizing predictive signals for both cross-sectional and time-series models
  • Strong experience with data exploration, dimension reduction, and feature engineering
  • Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity
  • Experience managing and running risk is a strong plus
  • Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc.
  • Creative mindset
  • Strong time management ability—the ability to manage multiple tasks and deadlines in a fast-paced environment
  • High degree of drive and energy—must be a self-starter
  • Ability to work cooperatively with all levels of staff and to thrive in a team-oriented environment
  • Commitment to the highest ethical standards and who act with professionalism and integrity at all times

The annual base salary range is $150000.00-$200000.00 (USD) . Actual compensation offered to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level among other things. Details about eligibility for bonus compensation (if applicable) will be finalized at the time of offer.

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