My client is a leading quant investment firm with offices globally. They deploy systematic trading strategies across asset class; including equities, futures, and foreign exchange. Researchers are responsible for conducting quantitative research using statistical and predictive modelling techniques.
Role/Responsibilities:
• Perform rigorous and innovative research to develop systematic signals for global futures (CME, Eurex, ICE, etc.) markets
• Perform feature engineering with price-volume and order book data at intraday horizons in high to mid frequency trading space (seconds to hours)
• Perform feature combination and monetization using various modeling techniques ranging from linear to machine learning models
• Manage 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
Requirements:
• MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics
• 2+ years of signal research experience in intraday futures / high frequency trading as part of a proprietary trading team
• Prior professional experience with feature engineering, modeling, or monetization
• Ability to efficiently format and manipulate large, raw data sources such as tick data
• Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
• Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques
• Collaborative mindset with strong independent research abilities
