Vice President, Senior Front Office Quant

We are seeking a Vice President, Senior Front Office Quant to join our team at RBC Capital Markets, LLC in New York.

The successful candidate will be responsible for applying quantitative and programming skills to research, develop, test, and implement securitized products and structured credit pricing / default / loss models. They will also build and maintain agency and non-agency mortgage prepayment and default models, and develop front office analytic tools for trading and risk.

Key responsibilities include:

• Collaborating with traders, risk managers, IT, and other functions to support trading activities
• Identifying operational risk/control deficiencies in the business
• Reviewing and complying with Firm Policies applicable to Central Funding Group (CFG) business activities
• Conducting data analysis, simulation, and forecasting with statistical and machine learning techniques
• Leveraging object-oriented programming (OOP) principles, utilizing C++, Python, and R programming languages to implement high-performance model libraries
• Integrating prepayment models into PolyPaths system with Intex
• Constructing and maintaining databases for ensuring persistence and availability of mortgage-backed securities data

Requirements:

• Master's degree in Financial Engineering, Quantitative Finance, Computational Finance & Risk Management, or a related field
• 4 years of related work experience
• 3 years of experience in using Python to develop and deploy quantitative models, build and maintain data pipelines, process large-scale datasets, and integrate with cloud computing environments
• 3 years of experience in automating analytics and reporting workflows for trading or financial applications
• 3 years of experience in using C++ to develop and maintain pricing and valuation libraries for fixed income or structured products
• 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
• 2 years of experience in modeling fixed income or structured products, including prepayment and credit risk modeling, Value-at-Risk calculations, loan performance transitions, duration and convexity analysis
• 1 year of experience in using SQL to query large datasets, support data pipelines, perform data extraction and transformation
• 1 year of experience in integrating database workflows with analytics or modeling platforms
• 1 year of experience in applying machine learning techniques, including classification and regression models, feature engineering

Benefits:

• Base salary of $210,000 per year
• Discretionary bonus
• 401(k) program with company-matching contributions
• Health, dental, vision, life, and disability insurance
• Paid time-off plan

Telecommuting is permitted up to 1 day per week.