Model Risk Analyst

Schedule

Overview

Hiring W@H in AZ, ID, NM, NV, TX, UT, VT, & WA

Models apply quantitative theories to process data into estimates, forecasts, and scores that are uncertain in nature, they inform decision making and can vastly improve efficiencies. The use of models introduces model risk, which is the potential for adverse consequences resulting from decisions based on model processes and output that may be incorrect or used inappropriately. The Model Risk Analyst plays a critical role in implementing and maintaining AFCU’s Model Risk Management (MRM) Program and works closely with model developers, model owners, model users, and other internal and external parties to identify, measure, monitor, and control model risk.

Responsibilities

• Work effectively as a team member while maintaining independence and objectivity to perform model validations and ensure timely remediation of identified issues. 
• Promote model risk management improvements, implement automated testing practices, and evaluate ongoing model performance. 
• Identify and maintain a centralized inventory of models, maintain the validation schedule and documentation library. 
• Help facilitate and implement the Credit Union’s MRM Program. 
• Track model performance KRIs and prepare appropriate dashboard and risk reporting. 
• Administer related software and manage third party relationships. 
• Identify emerging issues that relate to model risk. Maintain a working knowledge of applicable policies, procedures, and regulations. 
• Perform other duties as assigned. 

Qualifications

• Bachelor’s degree required in economics, mathematics, statistics, physics, finance, or related field, or 4 years of commensurate experience 
• Programming experience with Python, R, or similar computer languages 
• Strong SQL abilities and experience with both Oracle and Microsoft desired 
• Preferred experience in data science/analytics, risk management, model development/validation, model risk management, analytics software, relational databases, and/or big data for financial services 
• Knowledge of regulatory requirements related to model risk management 
• Understanding of statistical modeling, forecasting, machine learning, and data analytics 
• Excellent communication skills, verbal and written, with ability to translate complex statistical or economic theories and analysis into practical implications for business teams and management 
• Ability to work independently, as part of a team, and to lead. Strong work ethic.