Why This Role Stands Out
This VP-level Execution Quant Researcher role offers a fantastic opportunity to drive significant improvements in credit trading strategies within a leading investment firm, leveraging your expertise in market microstructure and quantitative modeling. You'll thrive here if you possess strong analytical skills and a deep understanding of credit markets, enjoying a hybrid work environment that fosters close collaboration with traders and portfolio managers. Apply to shape the future of execution research and make a tangible impact on fixed income portfolios.
Quick Overview
Job Description
Location: New York, NY
Overview
A leading investment firm is seeking a VP-level Quantitative Research Analyst to lead credit execution research and partner closely with traders and portfolio managers to improve execution outcomes across fixed income portfolios. This role combines quantitative research, market microstructure analysis, liquidity modeling, and transaction cost analysis to drive more efficient trading and decision-making.
Responsibilities
- Lead the credit execution research agenda, focusing on liquidity, market impact, counterparty selection, portfolio trading, execution protocols, and TCA.
- Develop quantitative models using trade, quote, and market data to improve execution performance.
- Serve as the primary research partner to credit traders and portfolio managers, translating business challenges into actionable research.
- Enhance execution analytics platforms through new models, datasets, and performance metrics.
- Monitor developments across credit market structure, electronic trading, and liquidity trends.
- Collaborate with researchers, developers, and trading teams to deploy research into production and drive adoption.
- Experience in quantitative research, trading, portfolio management, or market structure analysis within credit or fixed income markets.
- Strong understanding of credit market structure, including RFQ trading, portfolio trading, dealer behavior, ETF-driven liquidity, and transaction cost analysis.
- Experience working with fixed income datasets such as TRACE, quote data, evaluated pricing, and dealer inventory information.
- Strong statistical and analytical skills with the ability to solve complex, ambiguous problems.
- Knowledge of machine learning and AI applications within execution research.
- Excellent communication skills and ability to influence traders, portfolio managers, and senior stakeholders.
- Experience with rates or FX markets.
- Familiarity with Python, kdb+/q, Databricks, or similar data platforms.
- Experience working with dealers, trading venues, and market data vendors.
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