Model Governance Analyst

Job Duties
• Authoring and maintaining comprehensive documentation for key Treasury models (e.g., liquidity risk, market risk), ensuring compliance with internal Model Risk Management policies and regulatory standards.
• Leading MRM-related documentation activities, including the timely remediation of validator findings, and effectively bridging the gap between technical model developers and MRM’s requirements.
• Responsible for Model Ongoing Performance Monitoring (OPM) processes and reports.
• Managing the end-to-end documentation lifecycle for models, including maintaining standardized templates, version control, model change log, and coordinating review cycles with stakeholders (e.g., model owners and Model Risk teams).
• Identifying, researching, and proposing improvements to documentation processes, templates, and governance procedures to enhance quality and operational efficiency.
• Performing other financial analysis, research assignments, and other job duties as assigned.

Qualifications/Requirements
• 5+ years of proven experience in a quantitative role within financial industry, with a direct focus on model documentation, model validation, or model development. Experience specifically with Treasury models (e.g., Liquidity Risk, Interest Rate Risk) is a significant advantage.
• Bachelor’s degree required, preferably in a quantitative field (e.g., Economics, Finance, Mathematics, Statistics, Actuarial Science, Data Science).
• An advanced degree in a quantitative field and/or a professional certification directly related to financial risk management (such as CFA, FRM) is a strong plus.
• Exceptional technical writing and communication skills in English.
• Demonstrable understanding of financial products and the core principles of market risk, liquidity risk, and/or broader risk management.
• Proficiency with Microsoft Office suite is required.
• Meticulous attention to detail and a rigorous, analytical approach to problem-solving.
• Experience with statistical software (e.g., R, Python) or data tools (e.g., VBA, Power BI, SQL) is preferred.
• Strong project management skills, with the ability to manage the documentation lifecycle for multiple models simultaneously and meet strict deadlines.
• Excellent interpersonal skills, with the ability to collaborate effectively with quantitative model developers, validators, and other stakeholders.