VP Model Validation - Asset Management VP Model Validation - Asset Management …

Selby Jennings QRF
in Manhattan, NY, United States
Permanent, Full time
Last application, 14 May 21
Negotiable
Selby Jennings QRF
in Manhattan, NY, United States
Permanent, Full time
Last application, 14 May 21
Negotiable
Selby Jennings QRF
A leading international insurance company is building out their model validation team within Asset Management and is looking to hire an experienced model risk professional (VP level candidate). This role is on a small team validating Asset Management models used in their investment portfolios, including fixed income, structured products, real estate and equities.

A leading international insurance company is building out their model validation team within Asset Management and is looking to hire an experienced model risk professional (VP level candidate). This role is on a small team validating Asset Management models used in their investment portfolios, including fixed income, structured products, real estate and equities. This is a growing function and team that is led more by risk management requirements rather than regulatory requirements given their position in asset management. It is a lean function that is actively being invested in within the business with a lot of exposure and meaningful work to do.

Key Responsibilities:

Validating models and approaches used for investment portfolio models, including structured products, real estate, fixed income and equity investments

Participating in validation and risk assessments of models by using advanced data science techniques and innovative machine learning approaches

Communicating model validation conclusions to key stakeholders across the business and drafting comprehensive validation documentation for models validated

A Qualified Candidate Will Have:

At least 8 years of fulltime working experience in model validation or model development in asset management, banking, or insurance (big 4 consulting experience also applicable, internship experience excluded from the total years of experience)

At least a Masters of Science or another advanced degree in computer science, statistics, engineering, econometrics, physics or other quantitative discipline preferred

PhD is encouraged

Solid quantitative understanding of asset class risk characteristics

Understanding of investment market risk, finance, and regulatory aspects

Experience in at least 2 of the following: R, Python, Matlab, SAS, S-Plus, c++

Modeling experience in either structured products, interest rates, or counterparty risk analytics

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