Point72
Macro Quantitative Researcher
New York · Work style not stated
Posted over 6 months ago: check it’s still open
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About the role
Description from the employer’s posting. Check the employer’s page for the current version.
- EmployerPoint72
- LocationNew York
- Work styleWork style not stated
- Employer posted
About the Team:
A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional in the intraday to mid frequency systematic macro space. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.
Role:
- Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets
- Work with price-volume and alternative data at intraday to multiday (up to 2-3 weeks) horizons in the mid-frequency space
- Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
- Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets
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Responsibilities:
- Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets
- Alpha idea generation, backtesting, and implementation
- Evaluate new datasets for alpha potential
- Contribute to and enhance portfolio optimization, allocation and risk management processes
- Help drive the growth of the investment process and research capabilities of the team
- Assist in building, maintenance, and continual improvement of production and trading environments
Requirements:
- MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics
- 4+ years of signal research or portfolio management experience in futures markets and/or FX as part of a successful proprietary trading team with a track record
- Prior professional experience with signal combination, portfolio optimization and risk management
- Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
- Collaborative mindset with strong independent research abilities
- Commitment to the highest ethical standards
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At a glance
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