Company Overview
Our client is a leading firm that deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. Their core strength lies in rigorous research into a wide range of market anomalies, leveraging unparalleled access to diverse publicly available data sources.
Role
Our client is seeking a Quantitative Researcher to help build out their systematic macro (futures, FX, and vol) business. The primary focus will be on developing short-term to mid-frequency alpha strategies.
Responsibilities
- Develop systematic trading models across fixed income, currency, and commodity (FICC) markets.
- Manage the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation.
- Perform feature engineering with price-volume, order book, and alternative data for intraday to daily horizons in the mid-frequency trading space.
- Combine and monetize features using various modeling techniques.
- Assist in building, maintaining, and continually improving production and trading environments, coupled with execution monitoring.
- Contribute to the research infrastructure of the team.
Requirements
- Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics.
- 2-5 years of experience in macro quantitative trading, preferably FICC.
- Experience synthesizing predictive signals for both cross-sectional and time-series models driven by statistical/technical, fundamental, and data-driven signals.
- Ability to efficiently format and manipulate large, raw data sources.
- Strong experience with data exploration, dimension reduction, and feature engineering.
- Demonstrated proficiency in Python. Familiarity with data science toolkits, such as scikit-learn and Pandas. Experience with machine learning is a plus.
- Strong command of applied and theoretical statistics, linear algebra, and machine learning techniques.
- Collaborative mindset with strong independent research abilities.
- Commitment to the highest ethical standards.
