Quantitative Researcher MFT - Equity stat-arb

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. The successful candidate will be responsible for the full research lifecycle, from hypothesis generation and signal discovery through backtesting, implementation, and live performance evaluation. The team combines quantitative research, data science, and systematic trading to identify persistent sources of return across liquid financial markets. This role is suited to an individual who enjoys working in a highly research‑driven environment where ideas move quickly from development to production. 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 #J-18808-Ljbffr Selby Jennings