Quant Modelling Associate/vice President

JPMorgan Chase JPMorgan Chase · Banking · LONDON, United Kingdom · Corporate Sector

Quant Modeling Associate/Vice President role focused on end-to-end model risk management for electronic trading models at JPMorgan Chase. Responsibilities include evaluating model specifications, assumptions, testing, implementation, and performance metrics, as well as performing independent testing by replicating or building benchmark models. The role requires a strong quantitative background, experience in model validation or front office in electronic trading, and proficiency in Python.

What you'd actually do

  1. Evaluate conceptual soundness of model specifications, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability and comprehensiveness of performance metrics and risk measures. Perform independent testing of models by replicating or building benchmark models.
  2. Design and implement experiments to measure the potential impact of model limitations, parameter estimation errors, and deviations from model assumptions; compare model outputs with empirical evidence or outputs from model benchmarks.
  3. Evaluate the risks posed by non-transparent model parameters and/or non-linear relationships, and suggest ways to mitigate such risks.
  4. Document the model review findings and communicate them to stakeholders.
  5. Serve as the first point of contact for model governance related inquiries for the coverage area, and help identify and escalate issues to ensure that their resolutions are sound and timely.

Skills

Required

  • Master's or PhD in a quantitative discipline such as Mathematics, Physics, Engineering, Computer Science, Economics or Finance
  • Strong experience in model validation or front office in an area of electronic trading (either agency or market making)
  • Excellence in probability theory, stochastic processes, statistics, and numerical analysis.
  • Strong understanding of option pricing theory and quantitative models for derivatives.
  • Excellent communication skills (written and verbal)
  • Risk and control-oriented mindset: ability to ask incisive questions, assess materiality of model issues, and escalate issues appropriately.
  • Proficiency in Python (NumPy, SciPy, Pandas, etc).

Nice to have

  • Prior model validation or front‑office quant experience in pricing, risk, or electronic market making models.
  • Database interfacing, data management and (pre-)processing (kdb, q, SQL).
  • Experience of working with tensorflow and other ML packages.

What the JD emphasized

  • model validation
  • independent testing
  • quantitative discipline
  • quantitative models
  • model risk management
  • electronic trading