Senior Quantitative Analyst in Model Validation

  • Competitive
  • New York, NY, USA
  • Permanent, Full time
  • New York Life Insurance Company
  • 21 Mar 19

Senior Quantitative Analyst in Model Validation

A career at New York Life offers many opportunities. To be part of a growing and successful business. To reach your full potential, whatever your specialty. Above all, to make a difference in the world by helping people achieve financial security. It's a career journey you can be proud of, and you'll find plenty of support along the way. Our development programs range from skill-building to management training, and we value our diverse and inclusive workplace where all voices can be heard. Recognized as one of Fortune's World's Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and service, supported by our Foundation . It all adds up to a rewarding career at a company where doing right by our customers is part of who we are, as a mutual company without outside shareholders. We invite you to bring your talents to New York Life, so we can continue to help families and businesses "Be Good At Life." To learn more, please visit LinkedIn , our Newsroom and the Careers page of .

The Model Risk Management (MRM) team is responsible for the independent validation of the all models of the company, including actuarial (ALM, Valuation, Pricing), non-actuarial (investment), and models with actuarial and non-actuarial components.

The Senior Quantitative Analyst will be responsible for executing independent validation of a variety of models, including models with market and credit risks. Collaborating with members of the Model Risk Governance and the Model Validation teams, he/she will also assist in assessing and managing model risk and will contribute in developing an integrated method for validating models with interconnected insurance and non-insurance risks.


  • Lead and conduct model validations of the company's models based on internal Model Risk Management policies and procedures, regulatory guidance and industry best practices
  • Plan and oversee validation work to include evaluation of conceptual soundness and methodology, assumptions and limitations, data relevance and completeness, and outcome analysis
  • Collaborate with members of the MRM team to validate a variety of models, including models with intertwined financial and insurance risks
  • Work closely with model owners and model users to understand the models' use and business applications
  • Review and complete model validation reports, ensuring that they meet the Model Risk Governance standards
  • Communicate findings and recommendations to model owners and model users
  • Present findings to Senior Management and Model Risk Committee, as appropriate
  • Lead effort of building benchmark and test models used by model validation and monitoring
  • Contribute in monitoring model validation findings and evaluating remediation actions
  • Collaborate with the Lead of Model Risk Governance to ensure model governance and standards are appropriate for the firm's risk profile and are adhered to firm-wide

  • MS or higher degree in a quantitative discipline, such as, math, economics, statistics etc. preferred
  • Experience in model development and/or model validation
  • Experience working in risk areas, such as, risk, finance and/or regulation a plus
  • Team-oriented with a strong sense of ownership and accountability
  • Strong leadership, interpersonal and relationship management skills
  • Experience in documenting modeling approaches, techniques and validation practices
  • Familiarity with model documentation requirements that meet regulatory expectations
  • Strong verbal and written communication skills. Ability to review, critique and improve long reports and model documentation
  • Ability to become a trusted partner and implement change
  • Proven track record and demeanor to handle highly confidential and sensitive matters in changing environment
  • Experience with both banking and insurance models is a plus
  • Experience with at least one of the statistical and numerical programming languages, such as R, Python, MATLAB, SAS, S-Plus, C++

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