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Lead Model Validation Quantitative Analyst

Lead Model Validation Quantitative Analyst

  • Location Hungary - Central - Budapest
  • Travel required Yes - up to 10%
  • Job category Finance Group
  • Relocation available Negotiable
  • Job type Professionals
  • Job code 137735BR
  • Experience level Senior
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Job summary

Would you like to discover how our diverse, hardworking people are leading the way in making energy cleaner and better – and how you can play your part in our world-class team?

Join our team as a Lead Model Validation Quantitative Analyst

The Model Validation Team sits within Finance, Trading & Shipping and provides effective assurance of quantitative models. Our validation activities range from core valuation models used for derivative pricing, to validation of models used in the derivation of price/parameter input curves. The team’s operations span across Singapore, London, Chicago and Houston, covering T&S’s global Gas, Oil and Power trading activities.

As a senior analyst you will be 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.


In this role, You will:
  • 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


What You will need to be successful:

Essential education:
  • Bachelor’s degree and preferably PhD or MSc degree in a quantitative subject area, (e.g. physics, mathematics, electrical engineering or mathematical finance).

Practical experience of:
  • 5+ years of experience
  • Financial derivatives valuation methodologies and the fundamentals of trading including familiarity with financial instruments and physical assets
  • Knowledge in financial option pricing is preferred
  • C++ 17 and Python 3 programming languages
  • Stochastic calculus, probability theory and Levy processes, and associated numerical methods for their practical implementation
  • Dependency modeling, including copulas, cointegration and local correlation approaches
  • Optimization, stochastic control, stochastic dynamical programming and numerical linear algebra
  • Implementing advanced numerical algorithms
  • Practical methods of estimating computational complexity and expected algorithm performance
  • Experience with third-party libraries such as Boost, MKL, pybind11, NumPy and Pandas would be preferred
  • Ability to lead initiatives, influence and participate in decisions and collaborate effectively with commercial and functional partners

The following could be advantages:
  • Familiarity with the general principles of risk measurement and market risk metrics
  • Model Validation experience


At bp, we provide the following environment & benefits to you:
  • Different bonus opportunities based on performance, wide range of cafeteria elements
  • Life & health insurance, medical care package
  • Flexible working schedule: home office up to 2 days / week, based on team agreement
  • Opportunity to build up long term career path and develop your skills with wide range of learning options
  • Family friendly workplace
  • Employees’ wellbeing programs
  • Possibility to join our social communities and networks
  • Chill-out and collaboration spaces
  • Assets like phone for private usage and company laptop are provided

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