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Quantitative Risk Analyst

London, United Kingdom, £ £ - Annual Annual, Permanent


GAZPROM Germania GmbH is a subsidiary of the world's largest natural gas producer, Gazprom. Since its establishment in 1990, GAZPROM Germania has developed into an internationally operating group of 44 companies in 15 countries in Europe and Asia. Its main business activities include the storage and trading of natural gas. It employs approximately 1,800 employees, around 200 of whom work at its Berlin headquarters. Together with its strategic partners, GAZPROM Germania Group helps ensure a reliable, environmentally-friendly, and sustainable energy supply for Europe.

Gazprom Marketing & Trading (GM&T) is an integral part of the GAZPROM Germania Group. Headquartered in London, GM&T operates to provide a global marketing reach, round the clock operational coverage and excellent customer service. Established in 1999, GM&T has grown from a single office in London into a truly global organisation, with around 1000 employees worldwide. With offices in Europe, Asia and the USA, GM&T trades energy commodities including gas, power, oil, LPG, helium, emissions, LNG and FX.

Our culture is defined by our people. Through living our values every day we continue to create a culture that enables us all to succeed. We work as one team with our customers, our parent company and each other in order to understand each other's needs. With an unstoppable passion for excellence, growth and learning, we're committed to creating an environment that fosters the development of knowledge, skills and experience, so that our people can thrive and prosper in their careers with us. We believe that we have the best team in the industry which makes us a trusted partner across international capital and energy markets. Our diverse employee base, with a wealth of expertise, knowledge and experience makes GM&T a truly exciting place to work. We encourage new ideas and initiatives as innovative thinking is central to how we do business. Most importantly, we are a growing and developing business where inspired individuals can make a difference and help shape our future.

Role objectives

The team is responsible for validation of Python based models used by the traders and Risk as well as for the development, enhancements and maintenance of Python and C# based grid distributed Risk models.

The successful applicant is responsible for validation of front office valuation models and development of Risk models. The role will involve a wide range of quantitative tasks and candidates will need to demonstrate they have the range of technical and personal skills necessary to work within this challenging role.

Duties & Responsibilities

This involves (not limited to):

  • Validation of Front Office Python based valuation models used for trading and hedging
  • Contribute to the design and the development of an independent Risk model validation Python library
  • Create and develop Middle Office risk models
  • Participate in/lead Middle Office risk management projects
  • Respond to ad-hoc queries raised by the wider Risk team
  • Explain complex product modelling and valuation methodologies to the wider Risk team
  • Upgrade external packages the framework relies on and ensure existing functionality performs as expected
  • Maintain the existing suite of unit tests

Skills & Competencies

  • A strong analytic background, with experience of applying probability theory, stochastic calculus, time series and differential equation techniques to financial problems
  • In-depth understanding of Monte Carlo risk modelling methodologies - Market and Credit VaR, PFE and EaR.
  • Python programming skills
  • Experience with Github
  • Ability to communicate complex issues in an understandable manner to non-expert peers and senior management
  • Ability to work under pressure and to tight deadlines
  • Able to work as part of a team as well as individually


  • Experience in Monte Carlo modelling of Energy commodity derivatives within a trading environment is advantageous.
  • Risk modelling experience in Python or C# is desirable.


  • A PhD or Masters Degree level (or equivalent) in a highly quantitative subject.

Job Details

Not Specified
London, United Kingdom
£ £ - Annual Annual