Front Office Valuation & Structuring Quant, Gas & Power

Exxonmobil

England

On-site

GBP 120,000 - 190,000

Full time

6 days ago
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Benefits offered by this job

Competitive salary
Resettlement allowance
Pension scheme
Share plan
Private healthcare

Job summary

ExxonMobil in the United Kingdom invites applications for a Senior Front Office Quant role within the Valuation & Structuring team. You will provide independent valuation and risk assessment across gas storage, swing options, and power assets, supporting traders and originators.

You\'ll design pricing templates, model storage injections, and perform calibration, scenario analysis and back testing, collaborating with modelling and technology teams to deploy robust models into FO tools and asset

Qualifications

  • MSc/PhD preferred in quantitative fields such as maths, physics or engineering.
  • Front Office Gas & Power valuation/structuring experience.
  • Strong pricing and curve/vol modelling skills.
  • Advanced Python for pricing tools and analytics.
  • Ability to communicate complex valuation to traders.

Responsibilities

  • Provide fair valuation and independent risk assessment for gas and power assets and related structures.
  • Design and implement pricing templates and analytics tools.
  • Support traders in structure design, flows, and risk explanations.
  • Collaborate with modelling/tech teams to deploy robust models.

Skills

Valuation modelling
Python programming
Option pricing
Gas & Power valuation
Stochastic modelling

Education

MSc/PhD in quantitative field

Tools

Python

Job description

ExxonMobil in the United Kingdom invites applications for a Senior Front Office Quant role within the Valuation & Structuring team. You will provide independent valuation and risk assessment across gas storage, swing options, and power assets, supporting traders and originators.

You\'ll design pricing templates, model storage injections, and perform calibration, scenario analysis and back testing, collaborating with modelling and technology teams to deploy robust models into FO tools and asset

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