Essential Responsibilities:- (30%) Development and execution of policies, standards, and internal procedures for all phases of the model and AI life cycle, including identification, risk assessment, definition of control objectives, ongoing monitoring, and retirement.
- (20%) Ownership of the model risk management framework and reporting on model governance, development, validation, and monitoring for the organization. Responsible for creating and ongoing reporting of key risk indicators and management reporting for senior risk management stakeholders, management committees, and board-level committees.
- (20%) Design and maintain AI governance frameworks, standards, and research to guide responsible AI adoption. Embed responsible, transparent, and controlled AI practices across the full AI life cycle, from design and development to deployment and monitoring. Ensure that AI capabilities are delivered safely, ethically, and in alignment with regulatory expectations, while enabling speed, scalability, and business value. Partner with technology, privacy, operational, and compliance risk leaders to ensure AI risk practices are well-integrated.
- (10%) Manage and develop model risk and AI risk governance staff.
- (10%) Ensure overall compliance of the program with regulatory guidance on model risk management and artificial intelligence, staying current with changes in regulatory expectations and leading industry practices.
- (10%) Provide training and communication around the expectations of the MRM program and AI risk management to stakeholders across the organization.
Required Education & Experience (Knowledge, Skills, & Abilities):- Masters in a quantitative discipline (Economics, statistics, finance, data science or analytics, math, physics, or related field).
- 5+ years of experience in modeling or analytics, including experience developing enterprise-wide policies, standards and protocols in model risk, AI, or a related discipline.
- Ability to understand model conceptual design, testing of performance, controls over data flows, and compliance of model results with intended application.
- Must possess a deep understanding of regulatory guidance and expectations in Model Risk Management (e.g., SR 26-2, SR 15-19) and Artificial Intelligence (e.g. NIST AI Risk Management Framework, ISO 42001).
- Programming skills in a statistical programming language, such as SAS, R, or Python. Ability to independently write computer code to perform analysis on complex modeling and analytical challenges and to review code written by others for accuracy and efficiency.
- Subject matter expertise in advanced mathematical and statistical modeling techniques, such as competing risk logistic regression, time series analysis, ordinary least squares, Monte Carlo simulation, and machine learning techniques (e.g. XGBoost).
- Excellent oral and written communication skills. Experience writing and reviewing detailed technical validation reports and/or model development documentation.
- Familiarity with modern artificial intelligence (AI), including large language models (LLMs), retrieval augmented generation, generative AI, agentic AI, and the approaches and architecture required to harness and manage the risks of these tools.
- Strong attention to detail and the ability to independently formulate solutions to complex modeling and analytical challenges without existing procedures or precedent. Ability to mentor staff through complex analytical challenges and difficult technical conversations with internal and external stakeholders.
- Ability to evaluate model risks, weigh pros and cons of risk mitigation, and communicate very technical concepts in plain language.
- Perform job functions independently with limited day-to-day oversight from supervisor.
Preferred Education & Experience (Knowledge, Skills, & Abilities):- Experience managing teams of technical individual contributors and/or external vendors performing technical modeling work
- Experience in financial services or consulting industry
- Experience developing or validating models used for CECL, Credit Risk, CCAR/Stress Testing, PPNR, ALM, loan pricing and/or mortgage servicing rights, derivatives, Compliance (BSA/AML/OFAC), Liquidity, or Fraud
- Subject matter expertise in generative large language models (Artificial Intelligence)
- FRM or CFA certification
Job Environment & Physical Requirements:- Hybrid expectations
- Sitting for prolonged periods
- Computer for prolonged periods
DisclaimerState Employees' Credit Union reserves the right to fill this role at a higher/lower level based on business need.
