Head of Market Risk - LNG

NCAA, City of Westminster

Head of Market Risk - LNG

Salary not available. View on company website.

NCAA, City of Westminster

  • Full time
  • Permanent
  • Onsite working

Posted 1 day ago, 19 Dec | Get your application in today.

Closing date: Closing date not specified

job Ref: 98c2e9b981c84502aa98acdaaa1d19bc

Full Job Description

Summary: One of the largest Utility-backed physical energy traders in LNG, Coal and Freight is looking to add an experienced Market Risk Manager to lead the Risk team in London. The Risk Specialist will support the business in all key risk management matters affecting the organisation, including working alongside the traders - both challenging and supporting them on their daily activities. The Risk function forms part of our Middle Office and is responsible for the design of risk methodologies, implementation of suitable risk control frameworks and providing both qualitative and quantitative market risk analysis and risk control solutions.,

  • Develop and maintain engines for calculating VaR, CaR and PFE.
  • Conduct an in-depth quantitative analysis across the risk and credit functions, ensuring the models and portfolios are performing as intended.
  • As a leader in the risk control team, you will oversee all market risk activities, including the preparation of daily, weekly and monthly market risk reports, including but not limited to Value at Risk (VaR), sensitivities (the Greeks), stress testing, risk capital calculations, etc.
  • Provide support within the Market Risk team for the validation and development of risk models, including system testing and optimisation.
  • Support digitalization and automation to smooth the flow of information across the business and to remove manual task.
  • Leading the Market Risk Team, you will oversee the resourcing of the market risk activities and processes. The ability to manage, train / develop, coach and mentor the more junior members of the Market Risk Team will be critical.
  • Ability to enhance and optimise the Internalsystem and developing the quantitative and reporting tools used by the Credit department, Market Risk, Finance and Front Office teams.
  • Use a quantitative approach and analysis to support the risk control team on its methodologies - including limits (notional and vega), VaR back testing and assumptions.
  • Prepare analysis as directed by the head of the team for consideration by the Risk Committee and/or New Business Committee
  • Promote a culture of continuous improvement by leading, modelling and engaging in constructive challenge of existing processes. This includes looking at processes within the Market Risk Team, as well as shared processes and interfaces, collaboration and integration with Middle Office and Supporting Function teams.
  • Key liaison with Commercial / Front Office (Trading and Origination), Middle Office Functions (Product Control, Credit Risk, Internal Control, Legal, Compliance & Contracts, Treasury, etc.) and Shareholder departments.
  • Contribute to the design and implementation of a holistic risk control framework with focus on market risk
  • Support a risk conscious culture and promote best practice controls within the organisation through interaction with commercial and control teams across geographies

    A degree in Quantitative Finance, Mathematics, Physics, or other science disciplines.
  • 12 years' experience min. sitting in a similar position within a commodity trading house.
  • Communication skills - dealing with counterparts, senior management, internal/external regulators.
  • A background in risk management within an energy or commodity trading company, or Tier-1 investment bank.
  • Detailed knowledge of Value-at-Risk, scenario analysis, back testing / stress testing, expected shortfall, and other market risk techniques.
  • Knowledge of the market risk associated with physical commodities, traded and real option portfolios
  • Exposure to both physical and financial energy markets. - LNG, Gas, Power and Carbon
  • Knowledge of Allegro, FEA, Endur, Power BI, Matlab, SQL or other data analytics or quantitative analytics packages may be useful.