Senior Quantitative Risk Analyst

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SUMMARY: Reporting to the Risk Analytics and Reporting Manager, the Senior Quantitative Risk Analyst is part of the Credit Risk Reporting and Analytics team, a dynamic team of talented professionals whose task is to produce valuable recurring credit risk reporting and analytics as well as advance the modeling framework to identify and manage credit risk. The Senior Quantitative Risk Analyst uses a combination of quantitative, modeling, communication, and technical reporting skills to further advance the various risk analytics initiatives and add value to the organization by enhancing our credit risk modeling, monitoring, and reporting capabilities.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties and special projects may be assigned.

Ownership of third-party vendor credit loss models for CRE and C & I. This includes periodic analytical review of model performance and updates, as well as, maintaining internal model documentation consistent with internal and regulatory expectations.

Become a leading expert in the Moodys CMM, RiskCalc and RiskFrontier models.

Advance and refine our use of Moodys CMM, RiskCalc, RiskFrontier models. This includes using Moodys models and leveraging external and internal data to drive improvements in credit risk accuracy and utilizing the outputs to further stress testing, credit risk attribution, credit VaR, sensitivity analysis, and risk decomposition initiatives.

Contribute to the quarterly and annual end-to-end stress testing exercises. Conduct ad-hoc analysis as required. Develop potential stress scenarios that are meaningful to management.

Contribute to the integration of stress testing results into capital planning, capital allocation, and risk appetite frameworks.

Periodic reporting for CRE and C & I asset classes. This includes report generation in a wide variety of formats including but not limited to Tableau dashboards, Microsoft Excel report, PowerPoint presentations and Microsoft Word reports, on a periodic as well as ad-hoc basis.

Drive the automation of modeling routines as well as report and dashboard generation in a manner that drives consistency, accuracy and repeatability in credit risk reporting.

Contribute to the design and implementation of risk reporting across a variety of media.

Work closely with the data and technology teams to improve the data infrastructure needed to support the above initiatives.


To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.


Degree in a quantitative discipline (e.g. Statistics, Finance, Mathematics, Engineering, Economics).

4+ years experience in financial services (banking, asset management, insurance, etc) with significant direct exposure to analytics and modeling applied to credit risk and/or market risk.

Deep understanding of credit risk models (PD, LGD, VaR, etc). This Analyst should be able to use this understanding to provide expert insight into the credit risk results they report and enhance the modeling capabilities of the Credit Risk Reporting and Analytics team

Excellent communication skills (visual, verbal, and written) with the ability to articulate complex concepts into a format digestible by a diverse audience.

Experience in generating reports in Microsoft Word/Excel/PowerPoint and, ideally, in Tableau

Experience with programming languages, particularly R.

Proficiency with general quantitative modeling techniques (regression, simulation, optimization)

Experience utilizing and merging data from a variety of databases.

Strong interpersonal skills to aid in working with different divisions within the company.

Ability to work under pressure, meet deadlines, manage competing initiatives and adapt to an ever changing work pace with a focus on accuracy and attention to detail.


Advanced degree in a quantitative discipline (PhD or MSc in a STEM discipline or Economics/Finance)

Knowledge of latest modeling developments / trends

Experience with a wide assortment of financial modeling techniques, including but not limited to: credit losses, loss migration, interest rates, volatility, derivatives, VaR, prepayments, capital, forecast techniques, stress testing, scenario analysis, sensitivity analysis, RAROC, liquidity, FTP.

Prior experience in credit risk reporting.

Prior experience working with databases.

Prior experience automating tasks.

  • 1
  • Negotiable
  • None
  • None
  • Re-182809
  • Permanent
  • 0

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