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Tier-1 employer and metro location increase competition, but specialized quant/commodities skill narrows candidate pool.
Role is finance-specific market-risk modelling, making skills less transferable outside financial services.
Requires specific quantitative modelling, asset-class expertise and programming skills without explicit years, so moderately strict.
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Manage procurement, quality control, and governance of historical market data for key market risk metrics (e.g., VaR, Economic Capital, Stress Testing).
Develop and implement proxy methodologies and analytics to address gaps in historical market data, including for new risk factors post-IBOR migration.
Drive collaboration across Front Office, IT, and Risk to define and implement market data strategy, optimize infrastructure, and support regulatory and internal risk modelling requirements.
Degree in Engineering, Economics, Statistics, or similar numerate discipline.
Strong quantitative and analytical skills with demonstrated coursework in math/physics/statistics/engineering mathematics.
Programming skills in Matlab, Python, or equivalent, with demonstrated experience in numerical coding and implementation.
Work Experience Required: Not explicitly mentioned in the JD.
Experience with market risk models, especially in Commodities/Energy asset class risk modelling.
Ability to support model validation and recalibration of parameters for Value-at-Risk and other internal risk models.
Experience interacting with Front Office, Risk Methodology, and IT stakeholders to design and implement quantitative market data and risk solutions.