Vice President, Quantitative Financial Analyst

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

Quantitative Financial Analyst at Bank of America responsible for developing and implementing quantitative analytics and modeling projects for financial markets, with a focus on electronic trading systems for pricing, market making, and risk management in Global Rates. Requires strong quantitative background, Java development skills, and experience with production trading systems.

What you'd actually do

  1. Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
  2. Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
  3. Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
  4. Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
  5. Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk

Skills

Required

  • Java
  • multi-threaded programming
  • quantitative subject (Mathematics, Statistics, Physics, Engineering, Computer Science or other analytical background)
  • financial markets experience
  • quantitative modelling
  • working with large datasets
  • designing and building production trading systems
  • distributed low latency, high availability systems
  • pricing and risk management
  • trade & order lifecycle management
  • algorithmic execution

Nice to have

  • Google Guice or Spring
  • Masters/PhD level in a quantitative subject

What the JD emphasized

  • production trading systems
  • distributed low latency, high availability systems
  • pricing and risk management
  • trade & order lifecycle management
  • algorithmic execution
  • Java
  • multi-threaded programming
  • quantitative subject
  • financial markets experience
  • quantitative modelling
  • large datasets