Aso/VP – Quant Strategist – Credit

Aso/VP – Quant Strategist – Credit

Requirements

• Experience in both Python and C++ is highly desirable.
• As a minimum experience with object oriented programming and previous experience in either Python or C++ is required.
• Knowledge of working within a structured software development environment. Use of source code control systems, continuous integration environments, testing, release processes, etc.
• Knowledge of bond and credit derivative products, understanding of derivatives pricing models.
• Experience with large dataset analysis.
• PhD or Master’s degree in related field or equivalent work experience.

Responsibilities

• Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers.
• Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization.
• Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation.
• Supports model development and model risk management in respective focus areas to support business requirements and the enterprise’s risk appetite.
• Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk.
• Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes.
• Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches.
• Develop and maintain desk tools in Python.
• Develop the analytics library in C++.
• Support the trading desk with use of existing models, developing new strategies.
• Working on optimal portfolio selection and automated portfolio quoting.
• Analysis of large data sets and distilling the information contained within.
• Developing hedging strategies and backtesting their performance.
• Work closely with partners from other desks, e.g. XVA.
• Work closely with the technology team in order to deliver the analytics in the new system as well as improve performance where necessary.

Preferred Qualifications

• Critical Thinking
• Quantitative Development
• Risk Analytics
• Risk Modeling
• Technical Documentation
• Adaptability
• Collaboration
• Problem Solving
• Risk Management
• Test Engineering