Job Description
Mid/Low Frequency Quantitative Researcher – Systematic Trading
We are seeking a highly skilled Quantitative Researcher to join a systematic trading team, focusing on mid- and low-frequency strategies across global markets. The ideal candidate will have a strong background in statistical modeling, signal generation, and portfolio optimization, with a hands-on approach to research and implementation.
Responsibilities:
- Conduct research on alpha signals, market inefficiencies, and risk premia across equities, futures, and other asset classes.
- Develop and implement mid- and low-frequency trading strategies, balancing predictive power and execution costs.
- Work closely with portfolio managers and developers to integrate strategies into the trading pipeline.
- Utilize statistical and machine learning techniques to refine signal generation and risk management.
- Backtest and validate strategies using large-scale historical and real-time data.
- Optimize portfolio construction techniques to enhance risk-adjusted returns.
Requirements:
- Advanced degree (MSc/PhD) in a quantitative field such as Mathematics, Statistics, Computer Science, or Financial Engineering.
- 1+ years of experience in systematic trading, ideally focusing on mid/low-frequency strategies.
- Strong programming skills in Python and/or C++, with experience working in a research-driven environment.
- Deep understanding of statistical analysis, econometrics, and machine learning applied to financial markets.
- Hands-on experience with large-scale financial data, time-series modeling, and predictive analytics.
- Knowledge of market microstructure and execution strategies is a plus.
- Ability to work in a fast-paced, collaborative environment with strong attention to detail.
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