What You will do (essential responsibilities)

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

People leadership and team delivery

• Lead and develop a team of model governance professionals, including hiring, onboarding, coaching, performance reviews, and career development.
• Set clear goals, assign work, balance workloads, and manage team capacity to meet governance milestones and business priorities.
• Review team deliverables for accuracy, completeness, and consistency; provide technical guidance and resolve day-to-day delivery issues.
• Build a collaborative, accountable team culture that encourages sound judgment, continuous learning, and timely escalation of concerns.

Model governance oversight

• Oversee model governance documentation, ensuring model owners, purpose, and measurements remain accurate and current.
• Oversee standardized model documentation, including Model Cards, intended use, assumptions, limitations, known risks, explainability, and model evaluation metrics.
• Maintain a high-visibility process so that your team and other groups (management, engineering) can know the current state of model governance review at any time.
• Establish team metrics for completeness, review timeliness, documentation quality, and issue resolution; report progress, risks, and resource needs to leadership.
• Own the prioritization queue for model governance review, taking input from stakeholders on deadlines, from the team on time requirements, and communicate high-confidence deadline impacts when priorities are changed.
• Understand and communicate weaknesses in testing approaches when they are identified in model review, so that people elsewhere in the business are aware when metrics have low or high confidence.
• Ensure model data lineage and training, validation, and monitoring dataset records are maintained.
• Partner with model owners and observability team to define monitoring responsibilities, review triggers, and escalation paths; ensure model, data, or scope changes receive appropriate governance review.
• Track overdue reviews; escalate material risks, exceptions, and unresolved issues to the Director and relevant risk or compliance owners.

Cross functional partnership and improvement

• Coordinate governance priorities and dependencies with engineering, data science, risk, compliance, and product teams; represent the team externally, including to other managers.
• Oversee model review preparation, ensuring evidence is accessible and documentation is clear for technical and non-technical audiences.
• Improve governance workflows, templates, tools, and automation within established policies, and recommend broader changes to the Director. When changes from other teams are required, write those requests and be prepared to defend their value.

This job description reflects management’s assignment of essential functions; and nothing in this herein restricts management’s right to assign or reassign duties and responsibilities to this job at any time.

Managerial Responsibilities

Manager: Has authority to hire, develop, appraise, discipline and approve time and attendance for subordinates.

 

What You Need (Skills required)

Bachelor’s degree or higher in Computer Science, Engineering, Statistics, Mathematics, or a related technical or quantitative field.

Knowledge, skills, and abilities typically gained through 7+ years of experience in model governance, model validation, analytics, or related engineering roles, including 2+ years of direct people management.

Experience setting team priorities, coaching technical professionals, managing performance, and delivering work across multiple stakeholders.

Experience overseeing model documentation, approval workflows, controls, lifecycle tracking, and audit or governance reviews.

Strong understanding of AI/ML development, deployment, validation, benchmarking, and monitoring, with the ability to review technical implementations and guide governance decisions.

Experience using documentation and tracking tools to manage governance activities, and awareness of data privacy and security considerations.

Experience managing projects and workflows in Jira.

Experience managing documentation in Confluence.

 

Who You Are (Soft Skills & Attributes)

A people manager who sets clear expectations, provides practical feedback, and helps others grow.
A clear communicator and confident presenter who explains technical topics, risks, and priorities to varied audiences.
A collaborative partner who builds trust, resolves competing priorities, and follows through on commitments.
Organized and detail-oriented, with sound judgment, a focus on quality, and comfort working in risk-aware or regulated environments.

What Would Be Nice (Preferred Skills)

Working knowledge of Python and/or Java, SQL, databases, and common data formats such as CSV and JSON; ability to review datasets and technical evidence used in testing and validation.
Understanding of software development lifecycles, SDKs, APIs, integration patterns, and cloud environments such as AWS, Azure, or GCP.
Experience evaluating fraud, risk, or decisioning models.