Macro Quantitative Researcher
New YorkOn-siteFull-time
AI Summary
Quantitative researcher focused on developing systematic signals for global macro markets, from data processing to backtesting and production implementation in futures and FX. Works end-to-end within a collaborative research team.
About this role
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
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
Skills
Alternative DataBacktestingC/C++Data ProcessingPandasPortfolio OptimizationPythonRRisk ManagementSciKit-LearnSignal ProcessingTime-series Analysis
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