Quantitative Researcher, Credit eTrading - (Sr.) VP
Quantitative Researcher, Credit eTrading - (Sr.) VP
- Develop and enhance quantitative models in areas such as algorithmic trading, time series modeling, intraday risk management, and mid/reference price models for corporate bonds.
- Use data science and statistics to produce data-driven models for mid/reference pricing and facilitate market-making strategies for corporate bonds and loans.
- Collaborate closely with global traders to integrate quantitative strategies and model development into day-to-day trading decisions.
- Drive best practices in the design, roll-out, and adoption of systems to deliver real-time models and analytics.
- Work with Technology teams to execute and implement improvements in data collection, data intelligence, and overall model integration.
- Raise awareness of cutting-edge tools and technologies available to the trading desk and ensure their effective adoption.
- Manage at least one direct report, providing leadership, mentorship, and development opportunities for junior team members.
- Research, back-test, and report on ongoing model development efforts, ensuring clear explainability and ongoing improvements.
- Expertise in Algo/Time Series Modeling, Intraday Risk, Program Trading, or mid/reference price modeling for credit products.
- Proven experience in quantitative research and modeling within a front-office trading environment.
- Experience in managing teams or a strong interest in leadership, with at least one direct report.
- Strong mathematical, analytical, and problem-solving skills.
- Familiarity with mortgage or credit data, prepayment/default modeling, risk estimation, and market-making processes.
- Strong communication skills to present complex models and insights to both technical and non-technical stakeholders.
- Experience liaising with technology teams to improve model development, data systems, and infrastructure.
- 5-10 years of experience in quantitative research with a focus on algorithmic trading, time series modeling, or risk management.
- Strong background in credit products, including Corporate Bonds, Municipal Bonds, Leveraged Loans, and Credit Indices.
- Advanced proficiency in programming languages (e.g., Python, C++, R) and quantitative tools.
- Relevant degree(s) (e.g., PhD, MSc) in a quantitative discipline such as Mathematics, Physics, Engineering, or Finance.
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