Job Details

JOB DESCRIPTION

WHY IS THIS A GREAT OPPORTUNITY?

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Senior Quantitative Risk Manager

The Senior Quantitative Risk Manager is an internal client facing consultant and will focus on a wide variety of stimulating analytical projects, predominantly in asset/liability management (ALM), stress testing, risk measurement, valuation, and loan credit modeling. Outstanding candidates will have possess vast experience modeling the risks associated in numerous balance sheet classes throughout complex financial service environments.

JOB DESCRIPTION

Key Tasks:

• Develop & document quantitative models independently with a minimum of supervision.
• Research best practices and new modeling techniques.
• Responsible for development and analysis of quantitative models (financial and non-financial) focused on, but not limited to, forecasting, stress testing, valuation, interest rate modeling, and balance sheet management.
• Employ robust model development efforts to guarantee production of high-quality models.
• Facilitate the delivery of each model’s business objective(s).
• Partner with the model owner, model users, and model risk to safeguard that risks inherent in model development and usage are properly identified and managed.
• Support ensuing model validation efforts, and oversee model’s monitoring & maintenance over time.
• Create, review, and update strong and wide-ranging model documentation (methodology guide, user guide, policy documents).

QUALIFICATIONS

 Required:

5+ years of experience in a associated role in the industry is required.

Strong and fluent communication skills and the ability to confer ideas with colleagues at all levels of the organization is required.

Deep familiarity with database technology and integration of quantitative models within enterprise-scale software systems would be advantageous.

Acquaintance with a high level language such as C++ or Java, along with knowledge of numerical languages such as MATLAB or R is highly desired.

Profound familiarity with market risk methodologies such as Value-at-risk, back-testing, derivative pricing, statistical analysis and stress testing is vital. 

A robust quantitative background. A PhD in a quantitative field such as mathematics, physics, statistics or econometrics is mandatory. 

Education:
University - Bachelor's Degree/3-4 Year Degree