Front Office Quant Strat, Capital, Frtb - London, United Kingdom - Millar Associates
Description
London
Ref:
RCQD-1008
Total up to £250k + Benefits
Top-Tier Global Investment Bank
FRTB, Risk & Capital, Front Office Credit Quant Group
The Front Office Analytics Strat team at this Tier-1 Investment Bank is working to migrate all Global Markets businesses to the single strategic analytics platform and provides expertise in quant analytics, modeling, pricing and risk.
As an integral part of this Front Office team your focus will be on delivering cross-business functionality for Risk and Capital calculations.
KEY RESPONSIBILITIES:
- Development of a C++ quant library across Front Office, Risk, Finance and Treasury with a particular focus on the delivery of crossbusiness risk management and capital calculations.
- Development of crossbusiness risk and market databases, enabling all functions (Front Office & second line) to access risk and market data in a consistent taxonomy in the same analytical library.
- Depending on your quant / modelling expertise, contribute to the modelling and definition of risk & capital calculations and work with experienced quants on the implementation of these models.
- FRTB internal model (expected shortfall, default risk charge, nonmodellable risk factor charge).
- Development of bank's Market and Credit RWA processes, definition of proxies and construction of benchmarks and various analytic functions linked to the market data (calibrations, interpolation, observability, backtesting).
ESSENTIAL SKILLS & EXPERIENCE:
- Strong computing and programming (coding) skills, preferably C++ and Python.
- Experience of writing production code and a strong desire to continue doing this on a daytoday basis.
- Strong quantitative analytic, modeling, pricing and risk management skills and experience in financial services
- Strong numerical, mathematical and data modelling skills.
- Demonstrable experience of working as, or very closely with, FO Quants.
- MSc / PhD in Finance, Maths, Physics, Comp Sci, Econometrics, Stats or Engineering.
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