Sr. Model Governance Manager
New
J
JobgetherAI/ML governance
Based in the United StatesFull-TimeManager
Salary160,000 - 200,000 USD per year
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Job Details
- Experience
- At least 7 years of relevant experience in model governance, model validation, analytics, or related engineering roles; at least 2 years of direct people management experience.
- Required Skills
- AWSPythonSQLPeople ManagementJiraConfluence
Requirements
- Bachelor's degree or higher in Computer Science, Engineering, Statistics, Mathematics, or a related technical or quantitative discipline.
- At least 7 years of relevant experience in model governance, model validation, analytics, or related engineering roles.
- At least 2 years of direct people management experience, including setting priorities, coaching technical professionals, managing performance, and coordinating delivery across stakeholders.
- Experience overseeing model documentation, approval workflows, governance controls, lifecycle tracking, and audit or governance reviews.
- Strong understanding of AI/ML development, deployment, validation, benchmarking, and monitoring.
- Experience using documentation and tracking tools to manage governance activities, with awareness of data privacy and security considerations.
- Practical experience managing projects and workflows in Jira and maintaining documentation in Confluence.
- Strong people leadership skills, including setting expectations, providing constructive feedback, and supporting professional development.
- Working knowledge of Python and/or Java, SQL, databases, and common data formats such as CSV and JSON is preferred.
- Understanding of software development lifecycles, SDKs, APIs, integration patterns, and cloud environments such as AWS, Azure, or GCP is preferred.
- Experience evaluating fraud, risk, or decisioning models is preferred.
Responsibilities
- Lead, develop, and manage a team of model governance professionals, including recruitment, onboarding, coaching, performance reviews, and career development.
- Set team objectives, allocate responsibilities, balance workloads, and manage capacity against governance milestones and business priorities.
- Review team deliverables for accuracy, completeness, and consistency, providing technical guidance and resolving delivery challenges.
- Oversee model governance documentation, including model ownership, purpose, measurements, Model Cards, assumptions, limitations, risks, explainability, and evaluation metrics.
- Monitor governance review progress and performance metrics, communicating progress, risks, and resource needs to leadership.
- Own the model governance review prioritization queue and communicate the impact of priority changes.
- Partner with model owners and observability teams to define monitoring responsibilities, review triggers, and escalation paths.
- Track overdue reviews and escalate material risks, exceptions, and unresolved issues to the Director and relevant risk or compliance owners.
- Coordinate governance priorities with engineering, data science, risk, compliance, and product teams.
- Improve governance workflows, templates, tools, and automation within established policies.
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