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Quantitative Analyst for Systematic Trading
2 months ago
Point72 is a global asset management firm that utilizes systematic, data-driven trading strategies across various liquid asset classes, including equities, futures, and foreign exchange. Our mission is supported by extensive research into diverse market anomalies, leveraging our exceptional access to a multitude of publicly available data sources.
Position Overview
We are seeking a quantitative researcher to enhance our systematic macro strategies focusing on futures, foreign exchange, and volatility. The primary responsibility will involve developing mid-frequency alpha strategies.
Key Responsibilities
- Design and implement systematic trading models across foreign exchange, commodities, fixed income, and equity markets.
- Generate alpha ideas, conduct backtesting, and oversee implementation.
- Contribute to the development, maintenance, and ongoing enhancement of production and trading environments.
- Assess new datasets for their potential to generate alpha.
- Refine existing strategies and optimize portfolios.
- Monitor execution processes.
- Act as a vital contributor to the advancement of the investment process and research infrastructure within the team.
- Advanced degree (Masters or PhD) in mathematics, statistics, physics, or a related quantitative field; a PhD in statistics or machine learning is preferred.
- Experience in quantitative trading, particularly in foreign exchange or futures markets.
- Proficient in alpha research, portfolio construction, and optimization techniques.
- Skilled in developing statistical, technical, fundamental, and data-driven signals.
- Experience in synthesizing predictive signals for both cross-sectional and time-series models.
- Strong background in data exploration, dimensionality reduction, and feature engineering.
- Comprehensive understanding of various regression techniques, including OLS, MLS, Ridge, Lasso, and Bayesian inference, as well as methods for addressing issues like auto-correlation and heteroskedasticity.
- Experience in risk management is highly advantageous.
- Proficient in Python, particularly with the machine learning stack including numpy, pandas, and scikit-learn.
- Creative thinker with a strong ability to manage time effectively, balancing multiple tasks and deadlines in a dynamic environment.
- High energy and drive, demonstrating self-motivation.
- Able to collaborate effectively with all levels of staff and thrive in a team-oriented atmosphere.
- Committed to maintaining the highest ethical standards and professionalism at all times.
The annual base salary range for this position is $150,000-$200,000 (USD), exclusive of discretionary bonus compensation and our comprehensive benefits package. Actual compensation offered may vary based on geographic location, work experience, education, and skill level.
