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Job Title: Front Office Quantitative Analyst (C++ Expert)
Location: London
Working Model: Flexible WFH
Duration: 6 months - 12 months minimum with further extensions applicable
Daily Rate Available: up to £900 Umbrella
Inside IR35 via Umbrella: Paystream, Danbro, Focused
**Ideal candidate needs to have front office experience and C++ proficiency
ROLE DESCRIPTION
The role will require development of the underlying mathematical models and analytical tools used by the FX, Fixed Income, Credit, or Equities desks at HSBC
To design, develop, test and document the models developed to HSBC standards
Develop technical solutions for the desk as required
To provide rapid fixes to any issues identified in the models
To develop model calibration routines and market data analytics (such as curve bootstrapping and interpolation)Essential Knowledge and Experience Required
1-5 years working as a Quantitative Analyst developing models in quantitative finance, IT development, or a trading environment
A degree in mathematical finance, science or maths from a top tier university
Knowledge of the standard pricing models used in the investment banking industry
C++ experience (preferably using Visual Studio 2017)
Excel VBA experience required
Python experience preferred
Experience with IBOR a plus
Solid background in stochastic processes, probability and numerical analysis. Physics, Engineering or similar subjects is desirable, but not strictly required.
Knowledge of main instruments used in FX, Fixed Income, Credit, or Equities
Knowledge of CVA, CSA discounting, VaR, ES and other risk measures.
Strong C++
Knowledge of at least one of the following scripting languages: Python, Perl, Shell Script, C#, Java, VBA.
Good knowledge of Excel.
Knowledge of Windows and UNIX/LINUX, understanding of and experience with version control systems (GIT) and distributed development process.
Knowledge of distributed computing and serialisation techniques preferred.
Ability to work in fast-paced environment with proven ability to handle multiple outputs at one time
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