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Date Added: Sat 21/01/2023

Model Validation Quantitative Analyst

London, UK
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Job Type: Contract

Responsible for delivering practicable validations to models of various complexity. The role involves the development of reference valuation models, statistical/time-series data analysis and model parameter estimation and offers regular interaction with risk teams, traders, technology teams and Front Office quants at all levels and across all regions.

Client Details

A leading client in the Oil and Gas industry.


  • Perform efficient and effective validation of internal and third-party models.
  • Provide technical advice to commercial and control functions on the representation, valuation and risk measurement of deals involving optionality and/or illiquid assets.
  • Work closely with model users & developers to support and guide best practice for the mitigation of model risk within T&S.
  • Implement cross-commodity derivative valuation frameworks in bp's proprietary risk quantitative library, including new algorithms for stochastic process simulation, stochastic dynamical program solvers and calibration methodologies.
  • Employ modern software development practices for maintaining model correctness and performance.
  • Supervise and coach less experienced analysts in the team.


  1. Financial derivatives valuation methodologies and the fundamentals of trading including familiarity with financial instruments and physical assets.
  2. Stochastic calculus, probability theory and Levy processes, and associated numerical methods for their practical implementation, including advanced Monte Carlo methods, transform techniques and PDEs. To include local and stochastic volatility, jump and regime-switching models.
  3. Dependency modelling, including copulas, cointegration and local correlation approaches.
  4. Pricing in illiquid, incomplete markets. To include utility function-based approaches.
  5. Optimization, stochastic control, stochastic dynamical programming and numerical linear algebra.
  6. Implementing advanced numerical algorithms.
  7. Practical methods of estimating computational complexity and expected algorithm performance.
  8. C++ 17 and Python 3 programming languages, plus third-party libraries, including Boost, MKL, pybind11, NumPy and Pandas.

Job Offer

6 month contract

impressive day rate

hybrid working

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