Quantitative Risk Officer - Houston, Texas United States - 19884



JOB DESCRIPTION

Job #: 19884
Title: Quantitative Risk Officer
Job Location: Houston, Texas - United States
Employment Type:
Salary: $90,000.00 - $125,000.00 - US Dollars - Yearly
Employer Will Recruit From: Local
Relocation Paid?: NO

WHY IS THIS A GREAT OPPORTUNITY?


Quantitative Risk Officer opportunity

You will provide vital support to model development initiatives related to the quantitative analytic modeling program. 

JOB DESCRIPTION

Quantitative Risk Officer

Overview of Duties

  • Collaborate with the business and operation unit owners to discover and highlight risk associated with models and keep current with the newest developments in the current regulatory environment, risk technology (external and internal) and financial services industries in order to provide expert guidance to stakeholders.
  • Build or improve models to guarantee accuracy and relevancy in the current regulatory environment.
  • Lead the review of crucial model development and complete in depth analysis on large data sets.
  • Assist as a vital contributor and lead analyst supporting independent Quant model creation of capital planning and stress testing models.
  • Formulating analysis and reports to support discussions on crucial analytics and model risks.

QUALIFICATIONS

Quantitative Risk Officer - Required skills and education 

  1. Statistical tools including but not limited to SAS, Advanced Excel Macros, and SQL
  2. Master's degree or equivalent in: Statistics, Mathematics, Economics or related quantitative field is required
  3. Experienced in a statistical modeling risk analytics position.
  4. Three or more years of hands-on modeling experience with the following: Stress testing (DFAST, CCAR), capital planning, capital allocation, and/or funding and liquidity.
  5. Three or more years of statistical analysis and the handling of large volumes of data and analyzing for trends:
    1. Application of regulatory requirements for Model Risk.
    2. Modeling techniques supporting one the following: Capital Planning, Stress Testing (DFAST and/or CCAR), ALLL, Loss Forecasting, etc.
    3. Related experience in risk analytics/statistical modeling within the banking or financial industry.

Education:
University - Master's Degree

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