Senior Executive Director of Data & AI

Join JPMorganChase as a senior leader shaping the future of responsible data and AI governance at enterprise scale — where your expertise directly influences how one of the world's largest financial institutions innovates with integrity. In this high-visibility role, you will have the opportunity to build and lead a function that sits at the intersection of technology, risk, and regulatory strategy, with direct access to executive leadership and firm-wide impact.
As a Senior Executive Director of Data & AI at JPMorganChase within Employee Platforms, you will be responsible for establishing and overseeing the enterprise framework governing data, artificial intelligence, machine learning, analytics, and emerging AI technologies. You will lead the design, implementation, and continuous enhancement of governance, risk management, compliance, and control practices that ensure responsible, secure, transparent, and regulatory-compliant use of data and AI across the organization. This role serves as the senior liaison between Technology, Data Management, Cybersecurity, Risk, Compliance, Legal, Audit, and business stakeholders — enabling innovation while maintaining a robust risk and control environment.
Job responsibilities
Define and execute the firm's Data and AI Governance strategy and operating model, establishing policies, standards, procedures, and controls across data, analytics, AI, generative AI, machine learning, and agentic solutions
Lead governance for AI and generative AI initiatives throughout their full lifecycle, ensuring alignment with internal policies, model risk requirements, regulatory expectations, and responsible AI principles
Design and maintain an effective control environment across data and AI platforms, identifying, assessing, and mitigating operational, regulatory, privacy, cyber, model, and technology risks
Partner with technology teams to embed controls into data pipelines, AI platforms, and development lifecycles, and drive remediation of audit findings, regulatory observations, and control weaknesses
Monitor evolving global regulatory requirements impacting data and AI, coordinating regulatory examinations and internal audit reviews while serving as the senior escalation point for governance and compliance matters
Establish enterprise standards for data quality, lineage, metadata, classification, and access management, overseeing data quality monitoring, issue management, and exception reporting
Define governance practices for data access, entitlement management, and least-privilege principles, partnering with cybersecurity and platform teams to establish secure, scalable, and auditable access models
Chair or participate in governance forums responsible for AI and data oversight, presenting risk, control, and compliance metrics to executive committees
Lead and develop a high-performing team of governance, risk, controls, data management, and AI policy professionals, fostering a culture of accountability, innovation, and responsible AI adoption
Required qualifications, capabilities, and skills
Formal training or certification on technology risk and controls concepts and 10+ years applied experience
5+ years of senior leadership experience managing large-scale enterprise programs and cross-functional teams
Demonstrated expertise in data governance, AI and machine learning risk management, technology risk, operational risk, and internal controls
Proven experience designing and implementing governance frameworks for enterprise-scale data and AI ecosystems
Deep knowledge of data privacy, regulatory compliance, and audit and examination management within complex technology environments
Experience developing controls supporting AI explainability, transparency, fairness, bias monitoring, human oversight, and model performance management
Strong executive communication and stakeholder management skills, with the ability to influence senior leaders across technology, risk, compliance, and business functions
Preferred qualifications, capabilities, and skills
Advanced degree in Technology, Data Science, Business, Law, or Risk Management
Industry certifications such as Certified Data Management Professional (CDMP), Certified in Risk and Information Systems Control (CRISC), Certified Information Security Manager (CISM), or Certified Information Systems Security Professional (CISSP)
Experience with cloud and AI platforms such as AWS, Azure, or Databricks, including associated governance and compliance tooling
Prior experience in a highly regulated financial services organization with direct exposure to regulatory examinations and supervisory engagements
Familiarity with enterprise AI governance frameworks, responsible AI principles, and emerging global AI regulatory standards