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Director; Sr. Quantitative Finance Analyst

Director; Sr. Quantitative Finance Analyst

CompanyBank of America
LocationNew York, NY, USA
Salary$200000 – $210000
TypeFull-Time
DegreesMaster’s
Experience LevelSenior

Requirements

  • Master’s degree or equivalent in Engineering (any), Computer Science, Mathematics, Statistics or related
  • 5 years of experience in the job offered or a related Quantitative occupation
  • 5 years of experience in developing market risk or pricing models for financial products using time series and statistical analysis
  • 5 years of experience in applying time series analysis techniques to model market data dynamics
  • 5 years of experience in performing model diagnostic, reviewing model conceptual soundness and assessing model performance
  • 5 years of experience in using Python, C++, and object-oriented programming to write reusable and testable code
  • 5 years of experience in producing regulatory capital results and risk management metrics by following regulatory capital and risk management framework, and stress testing requirement.

Responsibilities

  • Develop quantitative risk models, analytics, and applications in support of market risk assessment and regulatory capital calculation
  • Conducting analysis and verification on market data, risk metrics, and P&L time series
  • Prepare developmental evidence and documentation to support internal and external exams
  • Perform in-depth analysis on the bank’s risk model results using various quantitative tools such as back testing, benchmarking, P&L attribution, and sensitivity analysis
  • Identify common themes across global markets along with improvement initiatives
  • Collaborate across teams including risk, capital, technology and model risk management for market risk time series analysis, data quality checking and thresholds determination and monitoring
  • Work on Stress testing for regulatory and market risk management purposes
  • Develop market risk or pricing models for financial products using time series and statistical analysis with understanding of risk drivers of price dynamics for financial products
  • Apply time series analysis techniques to model market data dynamics and to assess statistical inference and distribution
  • Perform model diagnostic, reviewing model conceptual soundness and assessing model performance
  • Use Python, C++, and object-oriented programming to write reusable and testable code to develop tools and improve process efficiency for reporting and calculation automation
  • Produce regulatory capital results and risk management metrics by following regulatory capital and risk management framework, and stress testing requirement.

Preferred Qualifications

    No preferred qualifications provided.