Quantitative Researcher MFT - Equity stat-arb

Overview

We are seeking an experienced Quantitative Researcher to join a systematic trading team focused on developing and scaling short-term, market-taking investment strategies. The role centers on alpha signal research across holding periods ranging from approximately 1 to 5 days, with a particular emphasis on statistical arbitrage, monetization, and portfolio construction.

Responsibilities

- Research and develop alpha signals for short-term systematic trading strategies with holding periods typically ranging from 1 to 5 days. - Design and implement statistical arbitrage models using large financial datasets and advanced quantitative techniques. - Conduct rigorous empirical research, including feature engineering, signal evaluation, portfolio construction, and risk analysis. - Develop predictive models using statistical methods and machine learning techniques where appropriate. - Build and enhance research infrastructure used for data analysis, simulation, and strategy development. - Perform robust backtesting and validation to assess signal stability, capacity, transaction cost impact, and out-of-sample performance. - Monitor live strategy performance and conduct attribution analysis to understand drivers of returns and evolving market dynamics. - Collaborate with quantitative researchers, traders, and engineers to transition research into production environments. - Continuously identify new datasets, methodologies, and research directions to improve performance and expand alpha opportunities.

Required Qualifications

- Advanced degree in a quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, Engineering, or a related field. - 5+ years of experience in quantitative research, systematic trading, statistical arbitrage, or alpha signal development. - Strong understanding of financial markets, market microstructure, and systematic investment processes. - Expertise in statistical modeling, time-series analysis, hypothesis testing, and predictive analytics. - Demonstrated experience developing and evaluating alpha signals in low signal-to-noise environments. - Strong programming skills in Python and experience with common data science and machine learning libraries. - Ability to conduct independent research and translate quantitative insights into implementable trading strategies. - Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications

- PhD or equivalent research experience in a quantitative field. - Experience researching short-term systematic strategies, including statistical arbitrage, cross-sectional modeling, and relative-value approaches. - Familiarity with machine learning applications for alpha generation and forecasting. - Experience working with large-scale datasets and distributed research environments. - Demonstrated track record of developing predictive signals that have contributed to live trading performance. - Understanding of portfolio optimization, execution considerations, transaction cost modeling, and capacity analysis.

Key Areas of Focus

- Alpha signal discovery - Statistical arbitrage research - Cross-sectional and time-series modeling - Short-term forecasting (1-5 day horizon) - Portfolio construction and risk management - Machine learning for financial prediction - Alternative and market data research - Systematic market-taking strategies - Performance attribution and strategy enhancement