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26 mo agofound 6 h ago
Quantitative Researcher - Macro
Posted by Point72 on 15 August 2024, 785 days ago. Still on their Greenhouse board when we checked 10 min ago.
Read out of the posting
LevelNot stated
Experience askedNot stated
EmploymentNot stated
LocationNew York
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2024-08-15
Found viagreenhouse, direct from their system
We saw it 26 months after it went up.
The posting, as the company wrote it
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
Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. 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
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 for this role is $150,000-$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.
Copied from Point72’s own board, not rewritten. Original ↗
Also open at Point72
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