MS or PhD in quantitative fields such as physics, engineering, statistics, or finance.
4+ years of quantitative research experience in a proprietary trading environment.
Strong knowledge of market microstructure, especially in futures or FX markets.
Experience in generating features from tick data and building statistical models.
Proficiency in programming languages like Python, R, or C/C++.
Ability to work collaboratively while demonstrating independent research skills.
Strong commitment to ethical standards.
Responsibilities
Conduct innovative research to create systematic trading signals for global macro markets.
Engage in feature engineering using order book tick data for various time horizons.
Implement modeling techniques, from linear models to machine learning.
Contribute to the complete research pipeline, from generating ideas to strategy backtesting and implementation.
Drive the growth and enhancement of the team’s investment process and research capabilities.
Collaborate with a skilled team and utilize advanced research and trading tools.
Support the development and maintenance of the trading and production environments.
Benefits
Access to cutting-edge research and trading infrastructure.
Opportunity to work with high-level professionals in a motivated team.
Resources provided for the expansion of quantitative macro business.
Environment encouraging continuous improvement and innovation.
Engagement in impactful research that contributes to team growth.
Full Job Description
About the Team:
A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional to develop and trade systematic macro strategies, with a focus on market microstructure. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.
Role/Responsibilities:
Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets, with a focus on market microstructure signals
Perform feature engineering with order book tick data at intraday to daily horizons
Perform feature combination using various modeling techniques ranging from linear to machine learning models
Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
Help drive the growth of the investment process and research capabilities of the team
Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets
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 experience in quantitative research, building statistical models for intraday to daily trading, as part of a successful proprietary trading team with a track record
Knowledge of market microstructure for futures and/or FX
Prior experience with tick data based feature generation, modelling, and monetization
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
About Point72
Point72 Asset Management is a hedge fund and family office founded by Steven Cohen in 2014. The company is headquartered in Stamford, Connecticut and manages over $16 billion in assets. Point72 primarily invests in public equity markets, but also has a private equity arm. The company has a global presence with offices in New York, London, Hong Kong, Tokyo, and Singapore. Point72 has been involved in several high-profile legal cases, including a $1.8 billion settlement with the SEC in 2013.
