Quantitative Researcher, Credit Market Making (IG Credit/Munis)

About the Role

Key Responsibilities

• Use statistical and machine learning techniques to develop real-time mid/reference price models for corporate bonds and municipal products.
• Build and maintain analytics libraries and systems that support pricing, liquidity, and execution decisions across Credit flow products.
• Conduct research, backtesting, and performance analysis of models; deploy production-grade solutions in collaboration with trading and technology teams.
• Partner with traders, market makers, and technologists to improve workflows, enhance model explainability, and drive adoption of analytics tools.
• Explore and apply modern AI/ML techniques to improve model robustness, scalability, and predictive power, especially in low-touch and systematic trading contexts.
• Ensure models and tools are aligned with trading objectives and contribute to P&L and risk management.

Requirements

• Advanced degree (PhD or Master's) in a STEM field such as Financial Engineering, Applied Mathematics, Computer Science, or Physics.
• Strong background in statistics, probability, and machine learning; familiarity with techniques such as parameter optimization, regularization, neural networks, and Gaussian processes.
• Hands-on experience with real-world datasets and practical data analysis.
• Deep understanding of Linear Credit instruments (Bonds, Loans, CDSs); experience with Municipal products is a plus.
• Strong programming skills in Python (pandas, NumPy, scikit-learn, TensorFlow, Spark, etc.).
• Experience with C++ or Java for production systems is preferred.
• Excellent communication and presentation skills; ability to summarize complex analysis for trading and management audiences.
• Proactive, detail-oriented, and comfortable working in a high-pressure, fast-paced environment.

Nice to Have

• Experience with reactive programming and real-time analytics systems.