Senior Quantitative Researcher

Title: Senior Quantitative ResearcherI am working with a NYC based prop group looking to onboard an experienced Senior Quant Researcher or Sub - PM to join an existing Global Equities Desk. This desk is headed by the firms founder who previously ran a multi-hundred-million dollar equities portfolio for a major tier 1 hedgfund. He is regarded as one of the best traders in this space and this this opportunity will allow work directly alongside him in their NYC office. This desk primarily focuses on US based markets deploying mid-frequency fully systematic Stat Arb signals.Responsibilities:Strategy Development: Generating new and optimizing existing statistical arbitrage signals for Mid-frequency (1 to 10 day holding periods) Global Equities strategiesTrading Execution: Execute mid-frequency trading strategies with a holding period of less than 10 days, ensuring high performance and profitability.Performance Monitoring: Continuously monitor and analyze the performance of trading strategies to ensure they meet the desired Sharpe Ratio and PnL targets.Risk Management: Implement robust risk management practices to mitigate potential losses and ensure the stability of trading strategies.Research and Analysis: Conduct in-depth research and analysis to identify new trading opportunities and enhance existing strategies.Collaboration: Work closely with other team members, including quants, developers, and traders, to ensure seamless strategy implementation and execution.Requirements:5+ Years in a similar Quantitative Research or Portfolio Management seatMaster's degree in Finance, Economics, Mathematics, Computer Science, Engineering, or a related field. PhD is a plus.Comprehensive knowledge of US/Global Equities modeling and tradingProven ability and comfort working with different groups (research, technology, operations) and with colleagues of varying experience levelsHigh attention to detail, excellent critical thinking, analytical abilities, and problem-solvingTechnical Experience: Hands on with Python and machine learning frameworks.

Created: 2025-01-15