Microstructure Quantitative Researcher at Point72

<p><strong><u>About the Team:</u></strong></p> <p>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.</p> <p><strong><u>Role/Responsibilities:</u></strong></p> <ul> <li>Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets, with a focus on market microstructure signals</li> <li>Perform feature engineering with order book tick data at intraday to daily horizons</li> <li>Perform feature combination using various modeling techniques ranging from linear to machine learning models</li> <li>Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation</li> <li>Help drive the growth of the investment process and research capabilities of the team</li> <li>Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets</li> <li>Assist in building, maintenance, and continual improvement of production and trading environments</li> </ul> <p><strong><u>Requirements: </u></strong></p> <ul> <li>MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics</li> <li>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</li> <li>Knowledge of market microstructure for futures and/or FX</li> <li>Prior experience with tick data based feature generation, modelling, and monetization</li> <li>Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas</li> <li>Collaborative mindset with strong independent research abilities</li> <li>Commitment to the highest ethical standards</li> </ul> <p>&nbsp;</p>