Model Risk Governance and Review Associate

MRGR (Model Risk Governance and Review) is a global team of modeling experts within the firm’s Risk Management and Compliance organization. The team is responsible for conducting independent model validation and model governance activities to help identify, measure, and mitigate model risk in the firm. The objective is to ensure that models are fit for purpose, used appropriately within the business context of their approval, and that model users are aware of any model risks or limitations which can impact business decisions.

As an Associate in MRGR Asset Management, you will be responsible for evaluating the risks associated with models used in Asset Management within the Asset & Wealth Management line of business. These models support a diverse range of business processes, including investment management, risk forecasting, stress testing, optimization, and factor-based investing strategies for alpha generation. The mathematical methodologies employed encompass multi-factor models for alpha and risk forecasting, pricing models for valuation and stress testing, optimization models utilizing numerical or analytical methods, linear/non-linear regression, and machine learning techniques. As part of the MRGR team, you will conduct independent testing, develop benchmarking tools, and monitor the performance of these models. You will apply your technical expertise and intellectual rigor to assess the conceptual soundness of various models and identify and evaluate emerging model risks from different component models and their interactions.

Job responsibilities

• Perform model reviews: analyze conceptual soundness of the models and assess model performance and suitability in the context of usage.
• Guide users regarding model usage and act as the first point of contact for the business on all new models and changes to existing models.
• Develop and implement alternative model benchmarks and compare the outcome of various models. Design model performance metrics.
• Liaise with model developers, users, and compliance groups, and provide guidance on model risk.
• Evaluate model performance on a regular basis.

Required qualifications, capabilities, and skills

• Minimum 2 years of experience in a quantitative modeling role such as data science, quantitative model development, or model validation for investment banks or similar financial institutions.
• A PhD or Master’s degree in a quantitative field such as Mathematics, Physics, Engineering, or Computer Science.
• Strong verbal and written communication skills, with the ability to interface with other functional areas in the firm on model-related issues and write high quality technical reports.
• Deep understanding of standard statistical techniques and probability theory.
• Experience with standard machine learning models, including Boosted Trees, Neural Networks, SVM, and LLM (e.g. BERT).
• Ability to code and implement models in Python, R, or equivalent.
• Risk and control oriented mindset: ability to ask incisive questions, assess the materiality of model issues, and escalate issues appropriately.
• Ability to work in a fast-paced, results-driven environment.

Preferred qualifications, capabilities, and skills

• Prior experience in developing or reviewing models used for asset management is desirable.
• Experience in reviews of machine learning models and Gen-AI type models is a plus.