Systematic Portfolio Trading and Credit Quant Position

Bank of America Bank of America · Banking · New York, NY

This role focuses on quantitative analytics and modeling for credit trading businesses at Bank of America, with a primary emphasis on systematic portfolio trading and a secondary focus on credit pricing analytics. Responsibilities include developing new models, analytic processes, systematic trading approaches, and desk-facing tools, as well as partnering with Technology for production deployment. The role requires a strong understanding of financial markets, credit products, quantitative judgment, and the ability to deliver robust analytics under tight timelines.

What you'd actually do

  1. Develop systematic pricing and risk management methods and trader tools that generate fast, explainable indicative ranges for bonds and portfolio trades, with clear diagnostics and practical desk controls.
  2. Create ETF create/redeem proposals, including basket construction, optimization, hedging recommendations, monitoring, and post-trade diagnostics for live trading workflows.
  3. Research, prototype, and productionize systematic portfolio trading strategies and algorithms, including automation, hedge selection, risk management, execution scheduling, and trading controls.
  4. Analyze large datasets across quotes, trades, holdings, constituents, liquidity, market data, and risk to improve tools, strategies, pricing accuracy, and trading outcomes.
  5. Support core credit pricing and risk analytics by contributing to model design, implementation, testing, release, production support, and integration into front-office platforms.

Skills

Required

  • Strong Python skills for quantitative research, data analysis, workflow automation, and production-quality desk tooling.
  • Solid understanding of credit bonds, portfolio trading mechanics, ETFs, liquidity, risk, hedging, and transaction-cost-aware decisioning.
  • Experience with systematic pricing, scenario analysis, and large-scale market or trading datasets.
  • Working knowledge of credit pricing and risk concepts used by trading desks, including model implementation, testing, and production support.
  • Strong software engineering discipline in structured SDLC environments, including version control, testing, CI/release processes, code reviews, and production support practices.
  • Excellent quantitative problem-solving skills, market intuition, communication ability, and judgment in p

Nice to have

  • C++ experience is preferred for performance-critical analytics and integration with core pricing libraries, though the role is primarily Python and systematic trading focused.