In addition to evaluating each candidate's relative ability, as demonstrated by quality and breadth of experience, the following factors will provide the basis for competitively evaluating each candidate:
1. Strategic Leadership
Demonstrated ability to set and lead enterprise-wide strategies spanning technology, data, and organizational considerations, including defining priorities, success measures, and an operating model that aligns with mission-driven goals. Experience applying this in complex, multi-department/entity environments is desirable.
2.Innovation Mindset and Emerging Technology Acumen
Ability to identify, assess, and leverage emerging technologies and analytics solutions to improve business outcomes, enhance public service delivery, and drive continuous improvement across a large enterprise. Capable of advancing innovation within environments that balance modernization with public accountability, equity, and policy considerations.
3. Enterprise Data Governance & Management Expertise
Deep experience in data governance, data quality, data integration, and enterprise data management to improve data usability, facilitate appropriate data sharing, advance data-informed decision-making, and support evidence-based programs and person-centered service delivery. Experience navigating the policy, privacy, and operational considerations common in governmental or other highly decentralized organizations is beneficial.
4. AI and Advanced Analytics Leadership
Demonstrated experience leading or overseeing the responsible development, deployment, and governance of AI and advanced analytics solutions, including alignment with enterprise architecture, security standards, and regulatory requirements. Ability to promote innovation and scalable adoption within mission-driven, risk-conscious environments such as public sector or other highly regulated organizations.
5. Policy, Ethics, and Regulatory Compliance Knowledge
Strong understanding of data and AI ethics, privacy, risk management, and compliance frameworks, with the ability to develop policies that ensure transparency, equity, and responsible use of data and AI. Experience applying these principles within a context where statutory, procurement, and regulatory oversight requirements are higher, such as public the public sector, is preferred.
6 Cross-Functional Leadership & Stakeholder Collaboration
Proven ability to build trust and lead collaboration across diverse stakeholder groups—including departments, executives, program leaders, researchers, and external partners—to foster a coordinated, person-centered data ecosystem. Able to effectively represent the organization in internal and external forums, including those involving government, community, and policy stakeholders.
7. Change Management & Workforce Development
Experience driving organizational culture change to strengthen data and AI literacy and readiness at scale. Skilled at developing training, supporting adoption of data governance and AI practices, and building a data-driven environment in settings with varying levels of digital and data maturity.