Senior AI Governance Specialist

About Northern Trust As a global leader in innovative wealth management, asset servicing, asset management and banking services, Northern Trust (Nasdaq: NTRS) is proud to guide the world’s most successful individuals, families, corporations and institutions. Since 1889, we have aligned our efforts with our three guiding Principles That Endure: Service, Expertise, and Integrity. Together, they reflect the three cornerstones of business conduct which we strive to instill in our employees, whom we call partners, and to provide to our clients and the communities we serve worldwide. With more than 135 years of financial experience and over 24,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service. Senior AI Governance Specialist, ASSET MANAGEMENT Northern Trust Asset Management (NTAM) is an over a trillion-dollar investment management firm entrusted by investors around the globe to help them navigate changing market environments, so they can confidently realize their long-term objectives.  NTAM has embarked on an ambitious plan to modernize its Data and AI capabilities and embed a data-driven culture throughout the organization. The Data Governance Specialist will pride themselves in taking a customer first approach to truly make it easier for our internal customers to protect, enhance and instill trust in our data to generate insight and deliver the best client experience.  The key focus of this role is to assist the company adopt AI quickly and safely. You will turn AI governance policy and standards into practical controls, assess AI use cases and models for risk, and give business teams clear guidance on what good looks like. You will work across Data, Technology, Risk, Legal and the business, reporting to the Head of Data and Analytics. KEY DUTIES AND RESPONSIBILITIES Support projects and establish responsible, safe AI practice across NTAM. Responsibilities include: Data management Check that data used in AI systems has a clear owner, documented lineage, quality checks and appropriate access controls. Explicit evaluation of data completeness, suitability, ownership, lineage, quality and governance Maintain the AI inventory and link each model to its source data, classification and retention requirements. Extend inventory coverage beyond models and use cases to AI systems, platforms, agents, agentic solutions, digital workers and vended AI capabilities  AI model risk management Work closely with the Enterprise Model Risk Management teams and Front line AI model governance team to run risk assessments on AI use cases and models, covering bias, explainability, privacy, security and third-party risk. Support model validation, ongoing monitoring and issue tracking in line with model risk principles (independent challenge, documentation, performance and drift thresholds).