• Vice President, Senior Front Office Quant, RBC Capital Markets, LLC, New York, NY: 

  Responsible to apply quantitative and programming skills to research, develop, test, and implement securitized products and structured credit pricing / default / loss models. Build and maintain agency and non-agency mortgage prepayment and default models. Build front office analytic tools for trading and risk. Effectively collaborate with traders, risk managers, IT and other functions to support trading activities. Identify operational risk/ control deficiencies in the business. Review and comply with Firm Policies applicable to Central Funding Group (CFG) business activities (funding, trading, and investment). Escalate operational risk loss events, control deficiencies and risks that are identified to line manager and the relevant control functions on a timely basis. Conduct data analysis, simulation and forecasting with statistical and machine learning techniques. Leverage object-oriented programming (OOP) principles, utilizing C++, Python and R programming languages to implement high performance model libraries. Integrate prepayment models into PolyPaths system with Intex. Construct and maintain databases for ensuring persistence and availability of mortgage-backed securities data (EMBS, Intex and CoreLogic).

  Telecommuting permitted up to 1 day per week.

  #LI-DNI

  Full time employment, Monday – Friday, 40 hours per week, $210,000.00 per year.

  MINIMUM REQUIREMENTS:

  Master’s degree in Financial Engineering, Quantitative Finance, Computational Finance & Risk Management or a related field and 4 years of related work experience.

  Must have 3 years of experience in:

  * Using Python to develop and deploy quantitative models, build and maintain data pipelines, process large-scale datasets, integrate with cloud computing environments.

  * Automate analytics and reporting workflows for trading or financial applications.

  * Using C++ to develop and maintain pricing and valuation libraries for fixed income or structured products, support legacy quantitative systems, implement unit testing, optimize performance. 

  * Analyze P&L attribution and valuation discrepancies.

  Must have 2 years of experience in:

  * Applying statistical and quantitative techniques, including regression analysis, Markov models, stochastic processes, time-series analysis, risk simulations, and model calibration and back-testing.

  * Modeling fixed income or structured products, including prepayment and credit risk modeling, Value-at-Risk calculations, loan performance transitions, duration and convexity analysis.

  * Option Adjusted Spread (OAS) - based relative value assessment. 

  Must have 1 year of experience in:

  * Using SQL to query large datasets, support data pipelines, perform data extraction and transformation.

  * Integrate database workflows with analytics or modeling platforms.

  * Applying machine learning techniques, including classification and regression models, feature engineering.

  * Model attribution, to financial or credit-related datasets.

  The base salary for this job is $210,000.00 per year. This salary does not include other elements of total compensation, including a discretionary bonus and benefits such as a 401(k) program with company-matching contributions; health, dental, vision, life and disability insurance; and paid time-off plan.

  RBC’s compensation philosophy and principles recognize the importance of a highly qualified global workforce and plays a critical role in attracting, engaging and retaining talent that:

  ·       Drives RBC’s high performance culture

  ·       Enables collective achievement of our strategic goals

  ·       Generates sustainable shareholder returns and above market shareholder value

  TO APPLY: Please click “Apply Now” Button

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Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

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