logo

Model Validation Quantitative Analyst Asset Management

  • Anywhere

Company :
New York Life Insurance Company

Location :
New York City, New York

Expiry Date :
Sun, 06 Dec 2020 23:59:59 GMT

Apply Job :
Open Link

Description :
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 Quantitative Analyst in Model Validation will be primarily responsible for independently validating models used in the investment portfolio of the company, including fixed income, structured products, real estate, equities etc. Reporting to the Lead of Asset Management Model Validation, the Quantitative Analyst will participate in developing appropriate metrics for measuring the risk of models in use by the asset management business of the company. In this capacity, the Quantitative Analyst will ensure that policies and standards are adhered to. In collaboration with members of the validation team, the Quantitative Analyst will also play a key role in supporting the company’s efforts in applying data science and machine learning. Description Of Responsibilities – Validate models and approaches used for investment portfolio models, including structured products, real state, fixed income, and equity investments – Participate in validation and risk assessment of models using advanced data science techniques, including new innovative machine learning approaches – Execute independent validation compliant with Model Risk Management policies and procedures, regulatory guidance and industry leading practices, including evaluating conceptual soundness, quality of modeling methodology, model limitations, data quality, and on-going monitoring – Draft comprehensive validation documentation for models validated – Communicate model validation conclusions to relevant stakeholders and evaluate model remediation actions – Collaborate with the Model Risk Governance team to ensure that model risk policies and standards are adhered to by business units Requirements – . or other advanced degree in computer science, statistics, engineering, econometrics, physics or other quantitative discipline preferred – Minimum 3 years of experience in model validation or model development in asset management, banking, insurance or consulting industry – Solid quantitative understanding of asset class risk characteristics – Experience in investment market risk, finance and regulatory aspects – Familiarity with industry-standard model documentation requirements – Team-oriented with a strong sense of ownership and accountability – Strong interpersonal and time management skills – Experience with two of the following numerical and statistical tools: R, Python, MATLAB, SAS, S-Plus, C++ – Experience with data science analytics and with handling large datasets in Python, R or equivalent is a plus EOE M/F/D/V If you have difficulty using or interacting with any portions of this Web site due to incompatibility with an Assistive Technology, if you need the information in an alternative format, or if you have suggestions on how we can make this site more accessible, please contact us at: . Job Requisition ID: 82807