Job #: 2489

Title: Quant Analyst


  • New York City, NY
  • Job Type:

  • Contract
  • Contract Pay Rate:
  • $50-75
    • Anywhere
    • Posted 11 months ago

    ​Role Summary & Responsibilities

    • Ability to evaluate and integrate 3rd party vendor prepayment model and has the ability to develop internal proprietary model if necessary
    • Experience in Mortgage prepayment and default modeling; credit, securitized and structured products. Agency/Non-Agency RMBS, CMBS, ABS (pricing, risk, VaR, stress testing, CCAR etc.).
    • Term structure modeling and risk-neutral valuation of mortgage backed securities (TBA, TBA Options/CMM, spec pools, CMOs and derivatives): curve fitting, interest rate models, volatility calibration, agency prepayment models.
    • good understanding of stochastic interest rate model and have ability to integrate internal interest rate model into mortgage platform
    • Advise and work with team to obtain new models approval to use from Model governance.
    • Advise if model as defined to support trading is fit for purpose of risk management requirements
    • Build quantitative tools to facilitate development, calibration, testing and validation of new prepayment models.
    • Support trading desk activities and build desk analytics tools

    Your experience and skills
    • MBS/RMBS/ABS/CMBS modeling, analytic and pricing. MBS prepayment model, default and loss models
    • Intex calc and Intex wrapper (API)
    • Extensive modeling knowledge and work experience with MBS, RMBS, CMBS, ABS and non-agency mortgages.
    • Proficient in statistical and econometrics modeling
    • Proficient in programing skill

    You are:
    • PHD in Finance, Engineering, or Computer Science
    • min 5 year experience in job offered or related fixed income quantitative research occupation with specialization in securitized and structured products for top-tier investment banks or asset management firms
    • with specific experience in C/C++, VBA, R, SAS, SQL, Oracle, Sybase, Intex , Intex Wrapper, Agency prepayment models and Loan performance data​


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