Associate Director, eFI Quant Trading, New York, NY
Core
Develop and implement low-latency algorithmic trading models, automated hedging algorithms, and trading strategies for US Treasury (UST) market making and electronic fixed income trading.
Role type
Senior IC quantitative trading engineer (fixed income/electronic trading)
Builds
Low-latency trading infrastructure, APIs, and automated market-making systems for US Treasuries
Domain
Fixed Income Capital Markets / Electronic Trading / Quantitative Finance
Deliverable
production ML models
Required skills
C++, Python, quantitative finance, low-latency system design, algorithmic trading, risk management, mathematical modeling (probability, statistics, linear algebra), back testing
Preferred skills
Machine Learning, Bayesian frameworks, cloud computing, GPU acceleration, distributed systems, KDB/Q, TensorFlow, Pytorch
Technologies
C++, Python, KDB/Q, SQL, Pandas, NumPy, TensorFlow, PyTorch, Scikit-learn
Responsibilities
Implement low-latency algorithmic trading models for UST Market Making; Develop and maintain automated hedging algorithms; Conduct alpha research and back testing for systematic strategies; Execute and monitor algorithmic strategies; Manage P&L and optimize execution quality
Seniority
Senior, hands-on IC