Market Risk Quantitative Research [multiple Positions Available]

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Corporate Sector

Develop and enhance mathematical market risk models for Value at Risk (VaR) metrics, execute performance testing, apply advanced quantitative methods, and ensure compliance with regulatory and internal governance requirements. This role involves working with derivatives, fixed income, liquidity, FX options, and structured products in Emerging Markets.

What you'd actually do

  1. Develop and enhance mathematical market risk models for Value at Risk (VaR) metrics for derivatives, fixed income, liquidity, FX options, and structured products for Emerging Markets.
  2. Execute performance testing of Value at Risk (VaR) models, assessing the impact of changes in pricing models, trading desk strategies, market environments, and regulatory requirements.
  3. Apply and develop advanced quantitative methods to ensure precise valuation and robust performance of VaR models, effectively addressing diverse market dynamics, new products, and evolving local regulatory changes across the Emerging Markets business.
  4. Deliver quantitative insights to market risk model stakeholders, including Market Risk senior management.
  5. Document and justify modeling choices, ensuring strict alignment with regulatory and internal governance requirements.

Skills

Required

  • Developing and enhancing mathematical market risk models for Value at Risk (VaR) metrics across derivatives, fixed income, liquidity products, FX options, and structured products in Emerging Markets
  • executing performance testing of VaR models and assessing the impact of pricing model changes, trading strategies, and regulatory shifts through scenario analyses
  • sourcing data from portfolio management systems and big-data platforms, and performing data extraction and processing using Tableau, Python, NumPy, SciPy, Pandas
  • applying Excel functions and business intelligence tools for sensitivity analysis and validation
  • documenting and justifying modeling choices to ensure compliance with regulatory requirements and internal governance standards
  • Managing market risk methodology for Value at Risk, scenario analysis from conceptualization to calibration by assessing their impact on accuracy against estimates, up to production
  • Performing quantitative maintenance of time-series data and model results and performance
  • Ensuring model compliance with model risk governance process and their usages within reliable, transparent, and auditable risk measurement
  • Managing and monitoring models that assess the accuracy of VaR risk factors to track the official portfolio risk and profit and loss through model accuracy
  • performing VaR performance analysis through backtesting against the official profit and loss
  • ensuring the proper operational functioning of risk management processes
  • Managing valuation and pricing software for quantitative analysis of trading portfolios covering derivatives, FX, options, fixed income, and liquidity products to ensure model consistency and identifying limitations relative to VaR models
  • maintaining and advancing market risk models, including Historical and Monte Carlo simulation models, Expected Shortfall, and Incremental VaR aggregation tools
  • Managing risk factor tools including aggregation of Greeks and higher-order sensitivities, and Profits and losses decomposition at the risk factor level
  • developing data infrastructure, including daily processing of VaR and FRTB jobs, simulation and proxy model libraries, and integrated API services for accessing risk data and analytics

What the JD emphasized

  • regulatory requirements
  • regulatory changes
  • regulatory
  • internal governance requirements
  • internal governance standards
  • model risk governance process
  • governance