Capital Markets - Developer x2

Typical Day in Role

• Champions a customer-focused culture to deepen client relationships and leverage broader client relationships, systems and knowledge.
• Develops valuation models for fixed-income products, and interest rate derivatives, and ensures the theoretical soundness, numerical accuracy, and implementation correctness of these models
• Develops robust, reliable and user-friendly front-office analytics for pricing, hedging, risk management and P&L attribution for both intraday and end-of-day
• Provides daily and on-demand quantitative support to the business in a timely manner related to valuation, risks, PnL attribution, hedging and so on
• Provides subject matter expertise to model stakeholders such as the business, risk management, audit, product control and technology groups during and post of the model implementation
• Forms a close partnership with the business to deliver models and analytics to production from end to end with limited supervision
• Understands how the client risk appetite and risk culture should be considered in day-to-day activities and decisions.
• Actively pursues effective and efficient operations of his/her respective areas, while ensuring the adequacy, adherence to, and effectiveness of day-to-day business controls to meet obligations with respect to operational risk, regulatory compliance risk, AML/ATF risk and conduct risk, including but not limited to responsibilities under the Operational Risk Management Framework, Regulatory Compliance Risk Management Framework, AML/ATF Global Handbook and the Guidelines for Business Conduct.
• Champions a high-performance environment and contributes to an inclusive work environment.

• 10+ years of progressive experience as an analyst/developer or similar capacity
• 3+ years’ experience in interest rate derivatives or fixed-income products and their valuation models
• Fluent with Python, and Unix Script, and Excel spreadsheets.

• Programming skills in C++, C++11 or higher version; experience with other programming languages such as Java, or Scala is preferred
• Solid background in PDE, Monte-Carlo and stochastic calculus is an asset

• PhD or Master’s Degree in Mathematics, Computer Science, Software Engineering, Physics or other quantitative areas