Job responsibilities:
- Evaluate conceptual soundness of model specifications, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability and comprehensiveness of performance metrics and risk measures
- Perform independent testing of models by replicating or building benchmark models
- Design and implement experiments to measure the potential impact of model limitations, parameter estimation errors, and deviations from model assumptions; compare model outputs with empirical evidence or outputs from model benchmarks
- Evaluate the risks posed by non-transparent model parameters and/or non-linear relationships, and suggest ways to mitigate such risks
- Document the model review findings and communicate them to stakeholders
- Serve as the first point of contact for model governance related inquiries for the coverage area, and help identify and escalate issues to ensure that their resolutions are sound and timely
- Provide guidance on the appropriate usage of models to model developers, users, and other stakeholders in the firm
- Stay abreast of the ongoing performance testing outcomes for models used in the coverage area, and communicate those outcomes to stakeholders
- Maintain the model inventory and model metadata for the coverage area
- Maintain the pace with the latest developments in coverage area in terms of products, markets, models, risk management practices, and industry standards
Required qualifications, capabilities, and skills :
- Master s degree in a quantitative discipline such as Math, Physics, Engineering, Computer Science, Economics or Finance - with minimum 3 years of relevant working experience or a PhD.
- Excellence in probability theory, stochastic processes, statistical/economic modeling, partial differential equations, and numerical analysis.
- Understanding of options and derivative pricing theory and risks
- Proficient in Python, R, Matlab, C++, or other programming languages
- Risk and control mindset: ability to ask incisive questions, assess materiality of model issues, and escalate issues appropriately
- Strong communication skills with the ability to interface with front office traders, and other functional areas in the firm on model-related issues; and produce documents for internal and external (regulatory) consumption
- Strong analytical and problem-solving abilities
Preferred qualifications, capabilities, and skills:
Knowledge of machine learning is not required but a plus.
