Senior Model Risk Manager – AI/ML

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Establish model governance protocols for AI/ML at Mercury.

• Continuously develop and improve frameworks for validation, monitoring, and governance.

• Oversee validation, monitoring, and governance of Mercury’s AI/ML model portfolio.

• Collaborate closely with data scientists, engineers, compliance leads, and product teams.

• Shape Mercury’s strategy for model risk management within the AI context.

• Conduct independent validation of predictive ML models and generative AI systems.

• Evaluate risks associated with LLM-powered applications and identify model limitations.

• Act as a trusted advisor throughout the AI/ML lifecycle.

• Contribute to the development of responsible AI standards, including explainability and bias assessment.

• Create AI-driven automation tools and modernize the Model Risk Management (MRM) function.

• Advocate for MRM as a strategic facilitator for AI/ML implementation across teams.

⛳️ Requirements

• Bachelor’s degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Mathematics, etc.) with 6-10 years of relevant hands-on experience in developing or validating AI/ML models and systems, preferably in financial services or fintech.

• Solid technical foundation in Python, SQL, and contemporary ML tools (e.g., scikit-learn, XGBoost).

• Knowledge of LLMs, RAG systems, prompt engineering, and AI agent frameworks.

• Experience in assessing and testing machine learning models (e.g., in fraud detection) and generative AI systems, including custom evaluations, red-teaming, or frameworks.

• Comprehensive understanding of model risk governance principles and regulatory expectations (e.g., SR 11-7 / OCC 2011-12, SR 26-2).

• Strong appreciation for disciplined model governance and independent effective challenge.

• A balanced skepticism paired with a constructive, solution-focused mindset.

• Ability to operate effectively in ambiguity: capable of synthesizing fragmented technical, operational, and business contexts into a coherent understanding of complex models and AI systems, making sound decisions even in the absence of a complete guide or perfect documentation.

• High level of agency and adaptability: able to function effectively in a dynamic environment where priorities shift rapidly, new ad hoc challenges arise frequently, and role boundaries are intentionally broad. Capable of identifying and executing high-impact work without a narrowly defined scope.

• Exceptional attention to detail in documentation, codebases, testing artifacts, and quantitative analysis.

• Excellent written and verbal communication skills; able to articulate model risk to both data scientists and regulators, using appropriate language for each audience.

🏝️ Benefits

• Base salary

• Equity

• Benefits